Publications – Aram Galstyan

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2022 (8)

Failure modes of domain generalization algorithms. Galstyan, T.; Harutyunyan, H.; Khachatrian, H.; Steeg, G. V.; and Galstyan, A. In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, pages 19077–19086, 2022.
link bibtex

@inproceedings{galstyan2022failure,
  title={Failure modes of domain generalization algorithms},
  author={Galstyan, Tigran and Harutyunyan, Hrayr and Khachatrian, Hrant and Steeg, Greg Ver and Galstyan, Aram},
  booktitle={Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition},
  pages={19077--19086},
  year={2022}
}

A Metric Space for Point Process Excitations. Marmarelis, M. G; Ver Steeg, G.; and Galstyan, A. Journal of Artificial Intelligence Research, 73: 1323–1353. 2022.
link bibtex

@article{marmarelis2022metric,
  title={A Metric Space for Point Process Excitations},
  author={Marmarelis, Myrl G and Ver Steeg, Greg and Galstyan, Aram},
  journal={Journal of Artificial Intelligence Research},
  volume={73},
  pages={1323--1353},
  year={2022}
}

Inferring topological transitions in pattern-forming processes with self-supervised learning. Abram, M.; Burghardt, K.; Ver Steeg, G.; Galstyan, A.; and Dingreville, R. npj Computational Materials, 8(1): 205. 2022.
link bibtex

@article{abram2022inferring,
  title={Inferring topological transitions in pattern-forming processes with self-supervised learning},
  author={Abram, Marcin and Burghardt, Keith and Ver Steeg, Greg and Galstyan, Aram and Dingreville, Remi},
  journal={npj Computational Materials},
  volume={8},
  number={1},
  pages={205},
  year={2022},
  publisher={Nature Publishing Group UK London}
}

Robust Conversational Agents against Imperceptible Toxicity Triggers. Mehrabi, N.; Beirami, A.; Morstatter, F.; and Galstyan, A. In Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, 2022.
link bibtex

@inproceedings{mehrabi2022robust,
  title={Robust Conversational Agents against Imperceptible Toxicity Triggers},
  author={Mehrabi, Ninareh and Beirami, Ahmad and Morstatter, Fred and Galstyan, Aram},
  booktitle={Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies},
  year={2022}
}

Formal limitations of sample-wise information-theoretic generalization bounds. Harutyunyan, H.; Ver Steeg, G.; and Galstyan, A. In 2022 IEEE Information Theory Workshop (ITW), pages 440–445, 2022. IEEE
link bibtex

@inproceedings{harutyunyan2022formal,
  title={Formal limitations of sample-wise information-theoretic generalization bounds},
  author={Harutyunyan, Hrayr and Ver Steeg, Greg and Galstyan, Aram},
  booktitle={2022 IEEE Information Theory Workshop (ITW)},
  pages={440--445},
  year={2022},
  organization={IEEE}
}

DEAM: Dialogue Coherence Evaluation using AMR-based Semantic Manipulations. Ghazarian, S.; Wen, N.; Galstyan, A.; and Peng, N. In ACL 2022, 2022.
link bibtex

@inproceedings{ghazarian2022deam,
  title={DEAM: Dialogue Coherence Evaluation using AMR-based Semantic Manipulations},
  author={Ghazarian, Sarik and Wen, Nuan and Galstyan, Aram and Peng, Nanyun},
  booktitle={ACL 2022},
  year={2022}
}

StATIK: Structure and text for inductive knowledge graph completion. Markowitz, E.; Balasubramanian, K.; Mirtaheri, M.; Annavaram, M.; Galstyan, A.; and Ver Steeg, G. In Findings of the Association for Computational Linguistics: NAACL 2022, pages 604–615, 2022.
link bibtex

@inproceedings{markowitz2022statik,
  title={StATIK: Structure and text for inductive knowledge graph completion},
  author={Markowitz, Elan and Balasubramanian, Keshav and Mirtaheri, Mehrnoosh and Annavaram, Murali and Galstyan, Aram and Ver Steeg, Greg},
  booktitle={Findings of the Association for Computational Linguistics: NAACL 2022},
  pages={604--615},
  year={2022}
}

Identifying geopolitical event precursors using attention-based LSTMs. Hossain, K. T.; Harutyunyan, H.; Ning, Y.; Kennedy, B.; Ramakrishnan, N.; and Galstyan, A. Frontiers in Artificial Intelligence, 5. 2022.
link bibtex

@article{hossain2022identifying,
  title={Identifying geopolitical event precursors using attention-based LSTMs},
  author={Hossain, KSM Tozammel and Harutyunyan, Hrayr and Ning, Yue and Kennedy, Brendan and Ramakrishnan, Naren and Galstyan, Aram},
  journal={Frontiers in Artificial Intelligence},
  volume={5},
  year={2022},
  publisher={Frontiers Media SA}
}
%2021

2021 (26)

Identifying and analyzing cryptocurrency manipulations in social media. Mirtaheri, M.; Abu-El-Haija, S.; Morstatter, F.; Ver Steeg, G.; and Galstyan, A. IEEE Transactions on Computational Social Systems, 8(3): 607–617. 2021.
link bibtex

@article{mirtaheri2021identifying,
  title={Identifying and analyzing cryptocurrency manipulations in social media},
  author={Mirtaheri, Mehrnoosh and Abu-El-Haija, Sami and Morstatter, Fred and Ver Steeg, Greg and Galstyan, Aram},
  journal={IEEE Transactions on Computational Social Systems},
  volume={8},
  number={3},
  pages={607--617},
  year={2021},
  publisher={IEEE}
}

A survey on bias and fairness in machine learning. Mehrabi, N.; Morstatter, F.; Saxena, N.; Lerman, K.; and Galstyan, A. ACM Computing Surveys (CSUR), 54(6): 1–35. 2021.
link bibtex 1 download

@article{mehrabi2021survey,
  title={A survey on bias and fairness in machine learning},
  author={Mehrabi, Ninareh and Morstatter, Fred and Saxena, Nripsuta and Lerman, Kristina and Galstyan, Aram},
  journal={ACM Computing Surveys (CSUR)},
  volume={54},
  number={6},
  pages={1--35},
  year={2021},
  publisher={ACM New York, NY, USA}
}

NERO: a biomedical named-entity (recognition) ontology with a large, annotated corpus reveals meaningful associations through text embedding. Wang, K.; Stevens, R.; Alachram, H.; Li, Y.; Soldatova, L.; King, R.; Ananiadou, S.; Schoene, A. M; Li, M.; Christopoulou, F.; and others NPJ systems biology and applications, 7(1): 1–8. 2021.
link bibtex

@article{wang2021nero,
  title={NERO: a biomedical named-entity (recognition) ontology with a large, annotated corpus reveals meaningful associations through text embedding},
  author={Wang, Kanix and Stevens, Robert and Alachram, Halima and Li, Yu and Soldatova, Larisa and King, Ross and Ananiadou, Sophia and Schoene, Annika M and Li, Maolin and Christopoulou, Fenia and others},
  journal={NPJ systems biology and applications},
  volume={7},
  number={1},
  pages={1--8},
  year={2021},
  publisher={Nature Publishing Group}
}

Muscle: strengthening semi-supervised learning via concurrent unsupervised learning using mutual information maximization. Xie, H.; Hussein, M. E; Galstyan, A.; and Abd-Almageed, W. In Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision, pages 2586–2595, 2021.
link bibtex 6 downloads

@inproceedings{xie2021muscle,
  title={Muscle: strengthening semi-supervised learning via concurrent unsupervised learning using mutual information maximization},
  author={Xie, Hanchen and Hussein, Mohamed E and Galstyan, Aram and Abd-Almageed, Wael},
  booktitle={Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision},
  pages={2586--2595},
  year={2021}
}

Discovering Higher-Order Interactions Through Neural Information Decomposition. Reing, K.; Ver Steeg, G.; and Galstyan, A. Entropy, 23(1): 79. 2021.
link bibtex 4 downloads

@article{reing2021discovering,
  title={Discovering Higher-Order Interactions Through Neural Information Decomposition},
  author={Reing, Kyle and Ver Steeg, Greg and Galstyan, Aram},
  journal={Entropy},
  volume={23},
  number={1},
  pages={79},
  year={2021},
  publisher={Multidisciplinary Digital Publishing Institute}
}

Discol: Toward engaging dialogue systems through conversational line guided response generation. Ghazarian, S.; Liu, Z.; Chakrabarty, T.; Ma, X.; Galstyan, A.; and Peng, N. In NAACL-HLT'21 (Demo Track), 2021.
link bibtex

@inproceedings{ghazarian2021discol,
  title={Discol: Toward engaging dialogue systems through conversational line guided response generation},
  author={Ghazarian, Sarik and Liu, Zixi and Chakrabarty, Tuhin and Ma, Xuezhe and Galstyan, Aram and Peng, Nanyun},
  booktitle={NAACL-HLT'21 (Demo Track)},
  year={2021}
}

Graph Traversal with Tensor Functionals: A Meta-Algorithm for Scalable Learning. Markowitz, E.; Balasubramanian, K.; Mirtaheri, M.; Abu-El-Haija, S.; Perozzi, B.; Steeg, G. V.; and Galstyan, A. In ICLR, 2021.
link bibtex

@inproceedings{markowitz2021graph,
  title={Graph Traversal with Tensor Functionals: A Meta-Algorithm for Scalable Learning},
  author={Markowitz, Elan and Balasubramanian, Keshav and Mirtaheri, Mehrnoosh and Abu-El-Haija, Sami and Perozzi, Bryan and Steeg, Greg Ver and Galstyan, Aram},
  booktitle={ICLR},
  year={2021}
}

A survey of human judgement and quantitative forecasting methods. Zellner, M.; Abbas, A. E; Budescu, D. V; and Galstyan, A. Royal Society open science, 8(2): 201187. 2021.
link bibtex

@article{zellner2021survey,
  title={A survey of human judgement and quantitative forecasting methods},
  author={Zellner, Maximilian and Abbas, Ali E and Budescu, David V and Galstyan, Aram},
  journal={Royal Society open science},
  volume={8},
  number={2},
  pages={201187},
  year={2021},
  publisher={The Royal Society}
}

Lawyers are Dishonest? Quantifying Representational Harms in Commonsense Knowledge Resources. Mehrabi, N.; Zhou, P.; Morstatter, F.; Pujara, J.; Ren, X.; and Galstyan, A. In Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing, 2021.
link bibtex

@inproceedings{mehrabi2021lawyers,
  title={Lawyers are Dishonest? Quantifying Representational Harms in Commonsense Knowledge Resources},
  author={Mehrabi, Ninareh and Zhou, Pei and Morstatter, Fred and Pujara, Jay and Ren, Xiang and Galstyan, Aram},
  booktitle={Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing},
  year={2021}
}

Influence Decompositions For Neural Network Attribution. Reing, K.; Ver Steeg, G.; and Galstyan, A. In International Conference on Artificial Intelligence and Statistics, pages 2710–2718, 2021. PMLR
link bibtex

@inproceedings{reing2021influence,
  title={Influence Decompositions For Neural Network Attribution},
  author={Reing, Kyle and Ver Steeg, Greg and Galstyan, Aram},
  booktitle={International Conference on Artificial Intelligence and Statistics},
  pages={2710--2718},
  year={2021},
  organization={PMLR}
}

Identifying botnet IP address clusters using natural language processing techniques on honeypot command logs. Crespi, V.; Hardaker, W.; Abu-El-Haija, S.; and Galstyan, A. arXiv preprint arXiv:2104.10232. 2021.
link bibtex

@article{crespi2021identifying,
  title={Identifying botnet IP address clusters using natural language processing techniques on honeypot command logs},
  author={Crespi, Valentino and Hardaker, Wes and Abu-El-Haija, Sami and Galstyan, Aram},
  journal={arXiv preprint arXiv:2104.10232},
  year={2021}
}

Bin2vec: learning representations of binary executable programs for security tasks. Arakelyan, S.; Arasteh, S.; Hauser, C.; Kline, E.; and Galstyan, A. Cybersecurity, 4(1): 1–14. 2021.
link bibtex

@article{arakelyan2021bin2vec,
  title={Bin2vec: learning representations of binary executable programs for security tasks},
  author={Arakelyan, Shushan and Arasteh, Sima and Hauser, Christophe and Kline, Erik and Galstyan, Aram},
  journal={Cybersecurity},
  volume={4},
  number={1},
  pages={1--14},
  year={2021},
  publisher={SpringerOpen}
}

q-Paths: Generalizing the geometric annealing path using power means. Masrani, V.; Brekelmans, R.; Bui, T.; Nielsen, F.; Galstyan, A.; Ver Steeg, G.; and Wood, F. In Uncertainty in Artificial Intelligence, pages 1938–1947, 2021. PMLR
link bibtex

@inproceedings{masrani2021q,
  title={q-Paths: Generalizing the geometric annealing path using power means},
  author={Masrani, Vaden and Brekelmans, Rob and Bui, Thang and Nielsen, Frank and Galstyan, Aram and Ver Steeg, Greg and Wood, Frank},
  booktitle={Uncertainty in Artificial Intelligence},
  pages={1938--1947},
  year={2021},
  organization={PMLR}
}

Domain Adaptation for Sentiment Analysis Using Increased Intraclass Separation. Rostami, M.; and Galstyan, A. arXiv preprint arXiv:2107.01598. 2021.
link bibtex

@article{rostami2021domain,
  title={Domain Adaptation for Sentiment Analysis Using Increased Intraclass Separation},
  author={Rostami, Mohammad and Galstyan, Aram},
  journal={arXiv preprint arXiv:2107.01598},
  year={2021}
}

Attributing Fair Decisions with Attention Interventions. Mehrabi, N.; Gupta, U.; Morstatter, F.; Steeg, G. V.; and Galstyan, A. arXiv preprint arXiv:2109.03952. 2021.
link bibtex

@article{mehrabi2021attributing,
  title={Attributing Fair Decisions with Attention Interventions},
  author={Mehrabi, Ninareh and Gupta, Umang and Morstatter, Fred and Steeg, Greg Ver and Galstyan, Aram},
  journal={arXiv preprint arXiv:2109.03952},
  year={2021}
}

Partner-assisted learning for few-shot image classification. Ma, J.; Xie, H.; Han, G.; Chang, S.; Galstyan, A.; and Abd-Almageed, W. In Proceedings of the IEEE/CVF International Conference on Computer Vision, pages 10573–10582, 2021.
link bibtex

@inproceedings{ma2021partner,
  title={Partner-assisted learning for few-shot image classification},
  author={Ma, Jiawei and Xie, Hanchen and Han, Guangxing and Chang, Shih-Fu and Galstyan, Aram and Abd-Almageed, Wael},
  booktitle={Proceedings of the IEEE/CVF International Conference on Computer Vision},
  pages={10573--10582},
  year={2021}
}

Information-theoretic generalization bounds for black-box learning algorithms. Harutyunyan, H.; Raginsky, M.; Ver Steeg, G.; and Galstyan, A. Advances in Neural Information Processing Systems, 34. 2021.
link bibtex

@article{harutyunyan2021information,
  title={Information-theoretic generalization bounds for black-box learning algorithms},
  author={Harutyunyan, Hrayr and Raginsky, Maxim and Ver Steeg, Greg and Galstyan, Aram},
  journal={Advances in Neural Information Processing Systems},
  volume={34},
  year={2021}
}

Cognitively Inspired Learning of Incremental Drifting Concepts. Rostami, M.; and Galstyan, A. arXiv preprint arXiv:2110.04662. 2021.
link bibtex

@article{rostami2021cognitively,
  title={Cognitively Inspired Learning of Incremental Drifting Concepts},
  author={Rostami, Mohammad and Galstyan, Aram},
  journal={arXiv preprint arXiv:2110.04662},
  year={2021}
}

Implicit SVD for Graph Representation Learning. Abu-El-Haija, S.; Mostafa, H.; Nassar, M.; Crespi, V.; Ver Steeg, G.; and Galstyan, A. Advances in Neural Information Processing Systems, 34. 2021.
link bibtex

@article{abu2021implicit,
  title={Implicit SVD for Graph Representation Learning},
  author={Abu-El-Haija, Sami and Mostafa, Hesham and Nassar, Marcel and Crespi, Valentino and Ver Steeg, Greg and Galstyan, Aram},
  journal={Advances in Neural Information Processing Systems},
  volume={34},
  year={2021}
}

Failure Modes of Domain Generalization Algorithms. Galstyan, T.; Harutyunyan, H.; Khachatrian, H.; Steeg, G. V.; and Galstyan, A. arXiv preprint arXiv:2111.13733. 2021.
link bibtex

@article{galstyan2021failure,
  title={Failure Modes of Domain Generalization Algorithms},
  author={Galstyan, Tigran and Harutyunyan, Hrayr and Khachatrian, Hrant and Steeg, Greg Ver and Galstyan, Aram},
  journal={arXiv preprint arXiv:2111.13733},
  year={2021}
}

Hamiltonian Dynamics with Non-Newtonian Momentum for Rapid Sampling. Ver Steeg, G.; and Galstyan, A. In Thirty-Fifth Conference on Neural Information Processing Systems, 2021.
link bibtex

@inproceedings{ver2021hamiltonian,
  title={Hamiltonian Dynamics with Non-Newtonian Momentum for Rapid Sampling},
  author={Ver Steeg, Greg and Galstyan, Aram},
  booktitle={Thirty-Fifth Conference on Neural Information Processing Systems},
  year={2021}
}

Layer-Wise Neural Network Compression via Layer Fusion. O’Neill, J.; Steeg, G. V; and Galstyan, A. In Asian Conference on Machine Learning, pages 1381–1396, 2021. PMLR
link bibtex

@inproceedings{o2021layer,
  title={Layer-Wise Neural Network Compression via Layer Fusion},
  author={O’Neill, James and Steeg, Greg V and Galstyan, Aram},
  booktitle={Asian Conference on Machine Learning},
  pages={1381--1396},
  year={2021},
  organization={PMLR}
}

Plot-guided Adversarial Example Construction for Evaluating Open-domain Story Generation. Ghazarian, S.; Liu, Z.; SM, A.; Weischedel, R.; Galstyan, A.; and Peng, N. In Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, 2021.
link bibtex

@inproceedings{ghazarian2021plot,
  title={Plot-guided Adversarial Example Construction for Evaluating Open-domain Story Generation},
  author={Ghazarian, Sarik and Liu, Zixi and SM, Akash and Weischedel, Ralph and Galstyan, Aram and Peng, Nanyun},
  booktitle={Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies},
  year={2021}
}

Exacerbating Algorithmic Bias through Fairness Attacks. Mehrabi, N.; Naveed, M.; Morstatter, F.; and Galstyan, A. In AAAI'21, 2021.
link bibtex

@inproceedings{mehrabi2021exacerbating,
  title={Exacerbating Algorithmic Bias through Fairness Attacks},
  author={Mehrabi, Ninareh and Naveed, Muhammad and Morstatter, Fred and Galstyan, Aram},
  booktitle={AAAI'21},
  year={2021}
}

One-shot learning for temporal knowledge graphs. Mirtaheri, M.; Rostami, M.; Ren, X.; Morstatter, F.; and Galstyan, A. In Automayed Knowledge Base Construction, AKBC 2021, 2021.
link bibtex

@inproceedings{mirtaheri2020one,
  title={One-shot learning for temporal knowledge graphs},
  author={Mirtaheri, Mehrnoosh and Rostami, Mohammad and Ren, Xiang and Morstatter, Fred and Galstyan, Aram},
  booktitle={Automayed Knowledge Base Construction, AKBC 2021},
  year={2021}
}

ForecastQA: A Question Answering Challenge for Event Forecasting with Temporal Text Data. Jin, W.; Khanna, R.; Kim, S.; Lee, D.; Morstatter, F.; Galstyan, A.; and Ren, X. In ACL 2021, 2021.
link bibtex

@inproceedings{jin2020forecastqa,
  title={ForecastQA: A Question Answering Challenge for Event Forecasting with Temporal Text Data},
  author={Jin, Woojeong and Khanna, Rahul and Kim, Suji and Lee, Dong-Ho and Morstatter, Fred and Galstyan, Aram and Ren, Xiang},
  booktitle={ACL 2021},
  year={2021}
}



%%2020

2020 (19)

Forecasting violent events in the middle East and North Africa using the hidden Markov model and regularized autoregressive models. Hossain, K. T.; Gao, S.; Kennedy, B.; Galstyan, A.; and Natarajan, P. The Journal of Defense Modeling and Simulation, 17(3): 269–283. 2020.
link bibtex

@article{hossain2020forecasting,
  title={Forecasting violent events in the middle East and North Africa using the hidden Markov model and regularized autoregressive models},
  author={Hossain, KSM Tozammel and Gao, Shuyang and Kennedy, Brendan and Galstyan, Aram and Natarajan, Prem},
  journal={The Journal of Defense Modeling and Simulation},
  volume={17},
  number={3},
  pages={269--283},
  year={2020},
  publisher={SAGE Publications Sage UK: London, England}
}

Stacking models for nearly optimal link prediction in complex networks. Ghasemian, A.; Hosseinmardi, H.; Galstyan, A.; Airoldi, E. M; and Clauset, A. Proceedings of the National Academy of Sciences, 117(38): 23393–23400. 2020.
link bibtex

@article{ghasemian2020stacking,
  title={Stacking models for nearly optimal link prediction in complex networks},
  author={Ghasemian, Amir and Hosseinmardi, Homa and Galstyan, Aram and Airoldi, Edoardo M and Clauset, Aaron},
  journal={Proceedings of the National Academy of Sciences},
  volume={117},
  number={38},
  pages={23393--23400},
  year={2020},
  publisher={National Academy of Sciences}
}

Man is to person as woman is to location: Measuring gender bias in named entity recognition. Mehrabi, N.; Gowda, T.; Morstatter, F.; Peng, N.; and Galstyan, A. In Proceedings of the 31st ACM Conference on Hypertext and Social Media, pages 231–232, 2020.
link bibtex

@inproceedings{mehrabi2020man,
  title={Man is to person as woman is to location: Measuring gender bias in named entity recognition},
  author={Mehrabi, Ninareh and Gowda, Thamme and Morstatter, Fred and Peng, Nanyun and Galstyan, Aram},
  booktitle={Proceedings of the 31st ACM Conference on Hypertext and Social Media},
  pages={231--232},
  year={2020}
}

Predictive engagement: An efficient metric for automatic evaluation of open-domain dialogue systems. Ghazarian, S.; Weischedel, R.; Galstyan, A.; and Peng, N. In Proceedings of the AAAI Conference on Artificial Intelligence, volume 34, pages 7789–7796, 2020.
link bibtex

@inproceedings{ghazarian2020predictive,
  title={Predictive engagement: An efficient metric for automatic evaluation of open-domain dialogue systems},
  author={Ghazarian, Sarik and Weischedel, Ralph and Galstyan, Aram and Peng, Nanyun},
  booktitle={Proceedings of the AAAI Conference on Artificial Intelligence},
  volume={34},
  number={05},
  pages={7789--7796},
  year={2020}
}

Improving generalization by controlling label-noise information in neural network weights. Harutyunyan, H.; Reing, K.; Ver Steeg, G.; and Galstyan, A. In International Conference on Machine Learning, pages 4071–4081, 2020. PMLR
link bibtex

@inproceedings{harutyunyan2020improving,
  title={Improving generalization by controlling label-noise information in neural network weights},
  author={Harutyunyan, Hrayr and Reing, Kyle and Ver Steeg, Greg and Galstyan, Aram},
  booktitle={International Conference on Machine Learning},
  pages={4071--4081},
  year={2020},
  organization={PMLR}
}

Anchor Attention for Hybrid Crowd Forecasts Aggregation. Huang, Y.; Abeliuk, A.; Morstatter, F.; Atanasov, P.; and Galstyan, A. arXiv preprint arXiv:2003.12447. 2020.
link bibtex

@article{huang2020anchor,
  title={Anchor Attention for Hybrid Crowd Forecasts Aggregation},
  author={Huang, Yuzhong and Abeliuk, Andr{\'e}s and Morstatter, Fred and Atanasov, Pavel and Galstyan, Aram},
  journal={arXiv preprint arXiv:2003.12447},
  year={2020}
}

Graph embedding with personalized context distribution. Huang, D.; He, Z.; Huang, Y.; Sun, K.; Abu-El-Haija, S.; Perozzi, B.; Lerman, K.; Morstatter, F.; and Galstyan, A. In Companion Proceedings of the Web Conference 2020, pages 655–661, 2020.
link bibtex

@inproceedings{huang2020graph,
  title={Graph embedding with personalized context distribution},
  author={Huang, Di and He, Zihao and Huang, Yuzhong and Sun, Kexuan and Abu-El-Haija, Sami and Perozzi, Bryan and Lerman, Kristina and Morstatter, Fred and Galstyan, Aram},
  booktitle={Companion Proceedings of the Web Conference 2020},
  pages={655--661},
  year={2020}
}

Modeling Dialogues with Hashcode Representations: A Nonparametric Approach. Garg, S.; Rish, I.; Cecchi, G.; Goyal, P.; Ghazarian, S.; Gao, S.; Ver Steeg, G.; and Galstyan, A. In Proceedings of the AAAI Conference on Artificial Intelligence, volume 34, pages 3970–3979, 2020.
link bibtex

@inproceedings{garg2020modeling,
  title={Modeling Dialogues with Hashcode Representations: A Nonparametric Approach},
  author={Garg, Sahil and Rish, Irina and Cecchi, Guillermo and Goyal, Palash and Ghazarian, Sarik and Gao, Shuyang and Ver Steeg, Greg and Galstyan, Aram},
  booktitle={Proceedings of the AAAI Conference on Artificial Intelligence},
  volume={34},
  number={04},
  pages={3970--3979},
  year={2020}
}

All in the exponential family: Bregman duality in thermodynamic variational inference. Brekelmans, R.; Masrani, V.; Wood, F.; Steeg, G. V.; and Galstyan, A. In ICML 2020, 2020.
link bibtex 3 downloads

@inproceedings{brekelmans2020all,
  title={All in the exponential family: Bregman duality in thermodynamic variational inference},
  author={Brekelmans, Rob and Masrani, Vaden and Wood, Frank and Steeg, Greg Ver and Galstyan, Aram},
  booktitle={ICML 2020},
  year={2020}
}

Sequential unsupervised domain adaptation through prototypical distributions. Rostami, M.; and Galstyan, A. . 2020.
link bibtex

@article{rostami2020sequential,
  title={Sequential unsupervised domain adaptation through prototypical distributions},
  author={Rostami, Mohammad and Galstyan, Aram},
  year={2020}
}

Robust Classification under Class-Dependent Domain Shift. Galstyan, T.; Khachatrian, H.; Steeg, G. V.; and Galstyan, A. arXiv preprint arXiv:2007.05335. 2020.
link bibtex

@article{galstyan2020robust,
  title={Robust Classification under Class-Dependent Domain Shift},
  author={Galstyan, Tigran and Khachatrian, Hrant and Steeg, Greg Ver and Galstyan, Aram},
  journal={arXiv preprint arXiv:2007.05335},
  year={2020}
}

Leveraging Clickstream Trajectories to Reveal Low-Quality Workers in Crowdsourced Forecasting Platforms. Matsui, A.; Ferrara, E.; Morstatter, F.; Abeliuk, A.; and Galstyan, A. arXiv preprint arXiv:2009.01966. 2020.
link bibtex

@article{matsui2020leveraging,
  title={Leveraging Clickstream Trajectories to Reveal Low-Quality Workers in Crowdsourced Forecasting Platforms},
  author={Matsui, Akira and Ferrara, Emilio and Morstatter, Fred and Abeliuk, Andr{\'e}s and Galstyan, Aram},
  journal={arXiv preprint arXiv:2009.01966},
  year={2020}
}

Quantifying machine influence over human forecasters. Abeliuk, A.; Benjamin, D. M; Morstatter, F.; and Galstyan, A. Scientific reports, 10(1): 1–14. 2020.
link bibtex

@article{abeliuk2020quantifying,
  title={Quantifying machine influence over human forecasters},
  author={Abeliuk, Andr{\'e}s and Benjamin, Daniel M and Morstatter, Fred and Galstyan, Aram},
  journal={Scientific reports},
  volume={10},
  number={1},
  pages={1--14},
  year={2020},
  publisher={Nature Publishing Group}
}

Likelihood ratio exponential families. Brekelmans, R.; Nielsen, F.; Makhzani, A.; Galstyan, A.; and Steeg, G. V. arXiv preprint arXiv:2012.15480. 2020.
link bibtex 3 downloads

@article{brekelmans2020likelihood,
  title={Likelihood ratio exponential families},
  author={Brekelmans, Rob and Nielsen, Frank and Makhzani, Alireza and Galstyan, Aram and Steeg, Greg Ver},
  journal={arXiv preprint arXiv:2012.15480},
  year={2020}
}

Annealed importance sampling with q-paths. Brekelmans, R.; Masrani, V.; Bui, T.; Wood, F.; Galstyan, A.; Steeg, G. V.; and Nielsen, F. arXiv preprint arXiv:2012.07823. 2020.
link bibtex 6 downloads

@article{brekelmans2020annealed,
  title={Annealed importance sampling with q-paths},
  author={Brekelmans, Rob and Masrani, Vaden and Bui, Thang and Wood, Frank and Galstyan, Aram and Steeg, Greg Ver and Nielsen, Frank},
  journal={arXiv preprint arXiv:2012.07823},
  year={2020}
}

Latent Embeddings of Point Process Excitations. Marmarelis, M. G; Steeg, G. V.; and Galstyan, A. arXiv preprint arXiv:2005.02515. 2020.
link bibtex

@article{marmarelis2020latent,
  title={Latent Embeddings of Point Process Excitations},
  author={Marmarelis, Myrl G and Steeg, Greg Ver and Galstyan, Aram},
  journal={arXiv preprint arXiv:2005.02515},
  year={2020}
}

Domain Agnostic Prototypical Distribution for Unsupervised Model Adaptation. Rostami, M.; and Galstyan, A. . 2020.
link bibtex

@article{rostami2020domain,
  title={Domain Agnostic Prototypical Distribution for Unsupervised Model Adaptation},
  author={Rostami, Mohammad and Galstyan, Aram},
  year={2020}
}

Learning a Max-Margin Classifier for Cross-Domain Sentiment Analysis. Rostami, M.; and Galstyan, A. . 2020.
link bibtex

@article{rostami2020learning,
  title={Learning a Max-Margin Classifier for Cross-Domain Sentiment Analysis},
  author={Rostami, Mohammad and Galstyan, Aram},
  year={2020}
}

Sequential Model Adaptation Using Domain Agnostic Internal Distributions. Rostami, M.; and Galstyan, A. arXiv preprint arXiv:2007.00197. 2020.
link bibtex

@article{rostami2020sequential,
  title={Sequential Model Adaptation Using Domain Agnostic Internal Distributions},
  author={Rostami, Mohammad and Galstyan, Aram},
  journal={arXiv preprint arXiv:2007.00197},
  year={2020}
}
%2019

2019 (14)

Multitask learning and benchmarking with clinical time series data. Harutyunyan, H.; Khachatrian, H.; Kale, D. C; Ver Steeg, G.; and Galstyan, A. Scientific data, 6(1): 1–18. 2019.
link bibtex

@article{harutyunyan2019multitask,
  title={Multitask learning and benchmarking with clinical time series data},
  author={Harutyunyan, Hrayr and Khachatrian, Hrant and Kale, David C and Ver Steeg, Greg and Galstyan, Aram},
  journal={Scientific data},
  volume={6},
  number={1},
  pages={1--18},
  year={2019},
  publisher={Nature Publishing Group}
}

Kernelized hashcode representations for relation extraction. Garg, S.; Galstyan, A.; Ver Steeg, G.; Rish, I.; Cecchi, G.; and Gao, S. In Proceedings of the AAAI Conference on Artificial Intelligence, volume 33, pages 6431–6440, 2019.
link bibtex

@inproceedings{garg2019kernelized,
  title={Kernelized hashcode representations for relation extraction},
  author={Garg, Sahil and Galstyan, Aram and Ver Steeg, Greg and Rish, Irina and Cecchi, Guillermo and Gao, Shuyang},
  booktitle={Proceedings of the AAAI Conference on Artificial Intelligence},
  volume={33},
  number={01},
  pages={6431--6440},
  year={2019}
}

Auto-encoding total correlation explanation. Gao, S.; Brekelmans, R.; Ver Steeg, G.; and Galstyan, A. In The 22nd International Conference on Artificial Intelligence and Statistics, pages 1157–1166, 2019. PMLR
link bibtex

@inproceedings{gao2019auto,
  title={Auto-encoding total correlation explanation},
  author={Gao, Shuyang and Brekelmans, Rob and Ver Steeg, Greg and Galstyan, Aram},
  booktitle={The 22nd International Conference on Artificial Intelligence and Statistics},
  pages={1157--1166},
  year={2019},
  organization={PMLR}
}

Coupled clustering of time-series and networks. Liu, Y.; Zhu, L.; Szekely, P.; Galstyan, A.; and Koutra, D. In Proceedings of the 2019 SIAM International Conference on Data Mining, pages 531–539, 2019. Society for Industrial and Applied Mathematics
link bibtex

@inproceedings{liu2019coupled,
  title={Coupled clustering of time-series and networks},
  author={Liu, Yike and Zhu, Linhong and Szekely, Pedro and Galstyan, Aram and Koutra, Danai},
  booktitle={Proceedings of the 2019 SIAM International Conference on Data Mining},
  pages={531--539},
  year={2019},
  organization={Society for Industrial and Applied Mathematics}
}

Debiasing community detection: The importance of lowly connected nodes. Mehrabi, N.; Morstatter, F.; Peng, N.; and Galstyan, A. In 2019 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM), pages 509–512, 2019. IEEE
link bibtex

@inproceedings{mehrabi2019debiasing,
  title={Debiasing community detection: The importance of lowly connected nodes},
  author={Mehrabi, Ninareh and Morstatter, Fred and Peng, Nanyun and Galstyan, Aram},
  booktitle={2019 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM)},
  pages={509--512},
  year={2019},
  organization={IEEE}
}

Exact rate-distortion in autoencoders via echo noise. Brekelmans, R.; Moyer, D.; Galstyan, A.; and Ver Steeg, G. In Advances in neural information processing systems, volume 32, 2019.
link bibtex

@inproceedings{brekelmans2019exact,
  title={Exact rate-distortion in autoencoders via echo noise},
  author={Brekelmans, Rob and Moyer, Daniel and Galstyan, Aram and Ver Steeg, Greg},
  booktitle={Advances in neural information processing systems},
  volume={32},
  year={2019}
}

Better automatic evaluation of open-domain dialogue systems with contextualized embeddings. Ghazarian, S.; Wei, J. T.; Galstyan, A.; and Peng, N. arXiv preprint arXiv:1904.10635. 2019.
link bibtex

@article{ghazarian2019better,
  title={Better automatic evaluation of open-domain dialogue systems with contextualized embeddings},
  author={Ghazarian, Sarik and Wei, Johnny Tian-Zheng and Galstyan, Aram and Peng, Nanyun},
  journal={arXiv preprint arXiv:1904.10635},
  year={2019}
}

Mixhop: Higher-order graph convolutional architectures via sparsified neighborhood mixing. Abu-El-Haija, S.; Perozzi, B.; Kapoor, A.; Alipourfard, N.; Lerman, K.; Harutyunyan, H.; Ver Steeg, G.; and Galstyan, A. In International Conference on Machine Learning, pages 21–29, 2019. PMLR
link bibtex

@inproceedings{abu2019mixhop,
  title={Mixhop: Higher-order graph convolutional architectures via sparsified neighborhood mixing},
  author={Abu-El-Haija, Sami and Perozzi, Bryan and Kapoor, Amol and Alipourfard, Nazanin and Lerman, Kristina and Harutyunyan, Hrayr and Ver Steeg, Greg and Galstyan, Aram},
  booktitle={International Conference on Machine Learning},
  pages={21--29},
  year={2019},
  organization={PMLR}
}

Efficient covariance estimation from temporal data. Harutyunyan, H.; Moyer, D.; Khachatrian, H.; Steeg, G. V.; and Galstyan, A. arXiv preprint arXiv:1905.13276. 2019.
link bibtex

@article{harutyunyan2019efficient,
  title={Efficient covariance estimation from temporal data},
  author={Harutyunyan, Hrayr and Moyer, Daniel and Khachatrian, Hrant and Steeg, Greg Ver and Galstyan, Aram},
  journal={arXiv preprint arXiv:1905.13276},
  year={2019}
}

Biorelex 1.0: Biological relation extraction benchmark. Khachatrian, H.; Nersisyan, L.; Hambardzumyan, K.; Galstyan, T.; Hakobyan, A.; Arakelyan, A.; Rzhetsky, A.; and Galstyan, A. In Proceedings of the 18th BioNLP Workshop and Shared Task, pages 176–190, 2019.
link bibtex

@inproceedings{khachatrian2019biorelex,
  title={Biorelex 1.0: Biological relation extraction benchmark},
  author={Khachatrian, Hrant and Nersisyan, Lilit and Hambardzumyan, Karen and Galstyan, Tigran and Hakobyan, Anna and Arakelyan, Arsen and Rzhetsky, Andrey and Galstyan, Aram},
  booktitle={Proceedings of the 18th BioNLP Workshop and Shared Task},
  pages={176--190},
  year={2019}
}

Fast structure learning with modular regularization. Ver Steeg, G.; Harutyunyan, H.; Moyer, D.; and Galstyan, A. Advances in Neural Information Processing Systems, 32. 2019.
link bibtex

@article{ver2019fast,
  title={Fast structure learning with modular regularization},
  author={Ver Steeg, Greg and Harutyunyan, Hrayr and Moyer, Daniel and Galstyan, Aram},
  journal={Advances in Neural Information Processing Systems},
  volume={32},
  year={2019}
}

Deep structured neural network for event temporal relation extraction. Han, R.; Hsu, I; Yang, M.; Galstyan, A.; Weischedel, R.; Peng, N.; and others In Proceedings of the 2019 SIGNLL Conference on Computational Natural Language Learning (CoNLL), 2019.
link bibtex

@inproceedings{han2019deep,
  title={Deep structured neural network for event temporal relation extraction},
  author={Han, Rujun and Hsu, I and Yang, Mu and Galstyan, Aram and Weischedel, Ralph and Peng, Nanyun and others},
booktitle={Proceedings  of the 2019 SIGNLL Conference on Computational Natural Language Learning (CoNLL)},
 year={2019}
}

SAGE: A Hybrid Geopolitical Event Forecasting System. Morstatter, F.; Galstyan, A.; Satyukov, G.; Benjamin, D.; Abeliuk, A.; Mirtaheri, M.; Hossain, K. T.; Szekely, P. A; Ferrara, E.; Matsui, A.; and others In IJCAI, volume 1, pages 6557–6559, 2019.
link bibtex

@inproceedings{morstatter2019sage,
  title={SAGE: A Hybrid Geopolitical Event Forecasting System.},
  author={Morstatter, Fred and Galstyan, Aram and Satyukov, Gleb and Benjamin, Daniel and Abeliuk, Andres and Mirtaheri, Mehrnoosh and Hossain, KSM Tozammel and Szekely, Pedro A and Ferrara, Emilio and Matsui, Akira and others},
  booktitle={IJCAI},
  volume={1},
  pages={6557--6559},
  year={2019}
}

Nearly-Unsupervised Hashcode Representations for Biomedical Relation Extraction. Garg, S.; Galstyan, A.; Ver Steeg, G.; and Cecchi, G. A In Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP), pages 4026–4036, 2019.
link bibtex

@inproceedings{garg2019nearly,
  title={Nearly-Unsupervised Hashcode Representations for Biomedical Relation Extraction},
  author={Garg, Sahil and Galstyan, Aram and Ver Steeg, Greg and Cecchi, Guillermo A},
  booktitle={Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP)},
  pages={4026--4036},
  year={2019}
}
%%2018

2018 (9)

Stochastic learning of nonstationary kernels for natural language modeling. Garg, S.; Steeg, G. V.; and Galstyan, A. arXiv preprint arXiv:1801.03911. 2018.
link bibtex

@article{garg2018stochastic,
  title={Stochastic learning of nonstationary kernels for natural language modeling},
  author={Garg, Sahil and Steeg, Greg Ver and Galstyan, Aram},
  journal={arXiv preprint arXiv:1801.03911},
  year={2018}
}

From alt-right to alt-rechts: Twitter analysis of the 2017 german federal election. Morstatter, F.; Shao, Y.; Galstyan, A.; and Karunasekera, S. In Companion Proceedings of the The Web Conference 2018, pages 621–628, 2018.
link bibtex

@inproceedings{morstatter2018alt,
  title={From alt-right to alt-rechts: Twitter analysis of the 2017 german federal election},
  author={Morstatter, Fred and Shao, Yunqiu and Galstyan, Aram and Karunasekera, Shanika},
  booktitle={Companion Proceedings of the The Web Conference 2018},
  pages={621--628},
  year={2018}
}

Modeling psychotherapy dialogues with kernelized hashcode representations: A nonparametric information-theoretic approach. Garg, S.; Rish, I.; Cecchi, G.; Goyal, P.; Ghazarian, S.; Gao, S.; Steeg, G. V.; and Galstyan, A. arXiv preprint arXiv:1804.10188. 2018.
link bibtex

@article{garg2018modeling,
  title={Modeling psychotherapy dialogues with kernelized hashcode representations: A nonparametric information-theoretic approach},
  author={Garg, Sahil and Rish, Irina and Cecchi, Guillermo and Goyal, Palash and Ghazarian, Sarik and Gao, Shuyang and Steeg, Greg Ver and Galstyan, Aram},
  journal={arXiv preprint arXiv:1804.10188},
  year={2018}
}

Mining and forecasting career trajectories of music artists. Arakelyan, S.; Morstatter, F.; Martin, M.; Ferrara, E.; and Galstyan, A. In Proceedings of the 29th on Hypertext and Social Media, pages 11–19. 2018.
link bibtex

@incollection{arakelyan2018mining,
  title={Mining and forecasting career trajectories of music artists},
  author={Arakelyan, Shushan and Morstatter, Fred and Martin, Margaret and Ferrara, Emilio and Galstyan, Aram},
  booktitle={Proceedings of the 29th on Hypertext and Social Media},
  pages={11--19},
  year={2018}
}

A Forest Mixture Bound for Block-Free Parallel Inference. Lawton, N.; Galstyan, A.; and Steeg, G. V. In Uncertainty in Artificial Intelligence (UAI), 2018.
link bibtex

@inproceedings{lawton2018forest,
  title={A Forest Mixture Bound for Block-Free Parallel Inference},
  author={Lawton, Neal and Galstyan, Aram and Steeg, Greg Ver},
  booktitle={Uncertainty in Artificial Intelligence (UAI)},
  year={2018}
}

Embedding networks with edge attributes. Goyal, P.; Hosseinmardi, H.; Ferrara, E.; and Galstyan, A. In Proceedings of the 29th on Hypertext and Social Media, pages 38–42. 2018.
link bibtex

@incollection{goyal2018embedding,
  title={Embedding networks with edge attributes},
  author={Goyal, Palash and Hosseinmardi, Homa and Ferrara, Emilio and Galstyan, Aram},
  booktitle={Proceedings of the 29th on Hypertext and Social Media},
  pages={38--42},
  year={2018}
}

Uncovering biologically coherent peripheral signatures of health and risk for Alzheimer’s disease in the aging brain. Riedel, B. C; Daianu, M.; Ver Steeg, G.; Mezher, A.; Salminen, L. E; Galstyan, A.; Thompson, P. M; Initiative, A. D. N.; and others Frontiers in aging neuroscience,390. 2018.
link bibtex

@article{riedel2018uncovering,
  title={Uncovering biologically coherent peripheral signatures of health and risk for Alzheimer’s disease in the aging brain},
  author={Riedel, Brandalyn C and Daianu, Madelaine and Ver Steeg, Greg and Mezher, Adam and Salminen, Lauren E and Galstyan, Aram and Thompson, Paul M and Alzheimer’s Disease Neuroimaging Initiative and others},
  journal={Frontiers in aging neuroscience},
  pages={390},
  year={2018},
  publisher={Frontiers}
}

Dialogue Modeling Via Hash Functions. Garg, S.; Cecchi, G. A; Rish, I.; Gao, S.; Ver Steeg, G.; Ghazarian, S.; Goyal, P.; and Galstyan, A. In LaCATODA@ IJCAI, 2018.
link bibtex

@inproceedings{garg2018dialogue,
  title={Dialogue Modeling Via Hash Functions},
  author={Garg, Sahil and Cecchi, Guillermo A and Rish, Irina and Gao, Shuyang and Ver Steeg, Greg and Ghazarian, Sarik and Goyal, Palash and Galstyan, Aram},
  booktitle={LaCATODA@ IJCAI},
  year={2018}
}

Invariant representations without adversarial training. Moyer, D.; Gao, S.; Brekelmans, R.; Steeg, G. V.; and Galstyan, A. In Advances in Neural Information Processing Systems (NeurIPS), 2018.
link bibtex

@inproceedings{moyer2018invariant,
  title={Invariant representations without adversarial training},
  author={Moyer, Daniel and Gao, Shuyang and Brekelmans, Rob and Steeg, Greg Ver and Galstyan, Aram},
  booktitle={Advances in Neural Information Processing Systems (NeurIPS)},
  year={2018}
}
%%2017

2017 (4)

Unifying Local and Global Change Detection in Dynamic Networks. Li, W.; Guo, D.; Steeg, G. V.; and Galstyan, A. arXiv preprint arXiv:1710.03035. 2017.
link bibtex

@article{li2017unifying,
  title={Unifying Local and Global Change Detection in Dynamic Networks},
  author={Li, Wenzhe and Guo, Dong and Steeg, Greg Ver and Galstyan, Aram},
  journal={arXiv preprint arXiv:1710.03035},
  year={2017}
}

Disentangled representations via synergy minimization. Ver Steeg, G.; Brekelmans, R.; Harutyunyan, H.; and Galstyan, A. In 2017 55th Annual Allerton Conference on Communication, Control, and Computing (Allerton), pages 180–187, 2017. IEEE
link bibtex 1 download

@inproceedings{ver2017disentangled,
  title={Disentangled representations via synergy minimization},
  author={Ver Steeg, Greg and Brekelmans, Rob and Harutyunyan, Hrayr and Galstyan, Aram},
  booktitle={2017 55th Annual Allerton Conference on Communication, Control, and Computing (Allerton)},
  pages={180--187},
  year={2017},
  organization={IEEE}
}

Highly Accurate Link Prediction in Networks Using Stacked Generalization. Ghasemian, A.; Galstyan, A.; and Clauset, A. . 2017.
link bibtex

@article{ghasemian2017highly,
  title={Highly Accurate Link Prediction in Networks Using Stacked Generalization},
  author={Ghasemian, Amir and Galstyan, Aram and Clauset, Aaron},
  year={2017}
}

Sifting Common Information from Many Variables. Ver Steeg, G.; Gao, S.; Reing, K.; and Galstyan, A. In IJCAI, pages 2885–2892, 2017.
link bibtex

@inproceedings{ver2017sifting,
  title={Sifting Common Information from Many Variables.},
  author={Ver Steeg, Greg and Gao, Shuyang and Reing, Kyle and Galstyan, Aram},
  booktitle={IJCAI},
  pages={2885--2892},
  year={2017}
}
%%2016

2016 (16)

The information sieve. Ver Steeg, G.; and Galstyan, A. In International Conference on Machine Learning, pages 164–172, 2016. PMLR
link bibtex

@inproceedings{ver2016information,
  title={The information sieve},
  author={Ver Steeg, Greg and Galstyan, Aram},
  booktitle={International Conference on Machine Learning},
  pages={164--172},
  year={2016},
  organization={PMLR}
}

Latent space model for multi-modal social data. Cho, Y.; Ver Steeg, G.; Ferrara, E.; and Galstyan, A. In Proceedings of the 25th International Conference on World Wide Web, pages 447–458, 2016.
link bibtex

@inproceedings{cho2016latent,
  title={Latent space model for multi-modal social data},
  author={Cho, Yoon-Sik and Ver Steeg, Greg and Ferrara, Emilio and Galstyan, Aram},
  booktitle={Proceedings of the 25th International Conference on World Wide Web},
  pages={447--458},
  year={2016}
}

Extracting biomolecular interactions using semantic parsing of biomedical text. Garg, S.; Galstyan, A.; Hermjakob, U.; and Marcu, D. In Thirtieth AAAI Conference on Artificial Intelligence, 2016.
link bibtex

@inproceedings{garg2016extracting,
  title={Extracting biomolecular interactions using semantic parsing of biomedical text},
  author={Garg, Sahil and Galstyan, Aram and Hermjakob, Ulf and Marcu, Daniel},
  booktitle={Thirtieth AAAI Conference on Artificial Intelligence},
  year={2016}
}

The DARPA Twitter bot challenge. Subrahmanian, V. S; Azaria, A.; Durst, S.; Kagan, V.; Galstyan, A.; Lerman, K.; Zhu, L.; Ferrara, E.; Flammini, A.; and Menczer, F. Computer, 49(6): 38–46. 2016.
link bibtex 10 downloads

@article{subrahmanian2016darpa,
  title={The DARPA Twitter bot challenge},
  author={Subrahmanian, Venkatramanan S and Azaria, Amos and Durst, Skylar and Kagan, Vadim and Galstyan, Aram and Lerman, Kristina and Zhu, Linhong and Ferrara, Emilio and Flammini, Alessandro and Menczer, Filippo},
  journal={Computer},
  volume={49},
  number={6},
  pages={38--46},
  year={2016},
  publisher={IEEE}
}

Relative value of diverse brain MRI and blood-based biomarkers for predicting cognitive decline in the elderly. Madsen, S. K; Ver Steeg, G.; Daianu, M.; Mezher, A.; Jahanshad, N.; Nir, T. M; Hua, X.; Gutman, B. A; Galstyan, A.; and Thompson, P. M In Medical Imaging 2016: Image Processing, volume 9784, pages 978411, 2016. International Society for Optics and Photonics
link bibtex

@inproceedings{madsen2016relative,
  title={Relative value of diverse brain MRI and blood-based biomarkers for predicting cognitive decline in the elderly},
  author={Madsen, Sarah K and Ver Steeg, Greg and Daianu, Madelaine and Mezher, Adam and Jahanshad, Neda and Nir, Talia M and Hua, Xue and Gutman, Boris A and Galstyan, Aram and Thompson, Paul M},
  booktitle={Medical Imaging 2016: Image Processing},
  volume={9784},
  pages={978411},
  year={2016},
  organization={International Society for Optics and Photonics}
}

Predicting online extremism, content adopters, and interaction reciprocity. Ferrara, E.; Wang, W.; Varol, O.; Flammini, A.; and Galstyan, A. In International conference on social informatics, pages 22–39, 2016. Springer, Cham
link bibtex

@inproceedings{ferrara2016predicting,
  title={Predicting online extremism, content adopters, and interaction reciprocity},
  author={Ferrara, Emilio and Wang, Wen-Qiang and Varol, Onur and Flammini, Alessandro and Galstyan, Aram},
  booktitle={International conference on social informatics},
  pages={22--39},
  year={2016},
  organization={Springer, Cham}
}

Using social media, online social networks, and internet search as platforms for public health interventions: a pilot study. Huesch, M. D; Galstyan, A.; Ong, M. K; and Doctor, J. N Health services research, 51: 1273–1290. 2016.
link bibtex

@article{huesch2016using,
  title={Using social media, online social networks, and internet search as platforms for public health interventions: a pilot study},
  author={Huesch, Marco D and Galstyan, Aram and Ong, Michael K and Doctor, Jason N},
  journal={Health services research},
  volume={51},
  pages={1273--1290},
  year={2016}
}

Toward interpretable topic discovery via anchored correlation explanation. Reing, K.; Kale, D. C; Steeg, G. V.; and Galstyan, A. arXiv preprint arXiv:1606.07043. 2016.
link bibtex

@article{reing2016toward,
  title={Toward interpretable topic discovery via anchored correlation explanation},
  author={Reing, Kyle and Kale, David C and Steeg, Greg Ver and Galstyan, Aram},
  journal={arXiv preprint arXiv:1606.07043},
  year={2016}
}

Scalable temporal latent space inference for link prediction in dynamic social networks. Zhu, L.; Guo, D.; Yin, J.; Ver Steeg, G.; and Galstyan, A. IEEE Transactions on Knowledge and Data Engineering, 28(10): 2765–2777. 2016.
link bibtex

@article{zhu2016scalable,
  title={Scalable temporal latent space inference for link prediction in dynamic social networks},
  author={Zhu, Linhong and Guo, Dong and Yin, Junming and Ver Steeg, Greg and Galstyan, Aram},
  journal={IEEE Transactions on Knowledge and Data Engineering},
  volume={28},
  number={10},
  pages={2765--2777},
  year={2016},
  publisher={IEEE}
}

Emergence of leadership in communication. Allahverdyan, A. E; and Galstyan, A. PloS one, 11(8): e0159301. 2016.
link bibtex

@article{allahverdyan2016emergence,
  title={Emergence of leadership in communication},
  author={Allahverdyan, Armen E and Galstyan, Aram},
  journal={PloS one},
  volume={11},
  number={8},
  pages={e0159301},
  year={2016},
  publisher={Public Library of Science San Francisco, CA USA}
}

Unsupervised entity resolution on multi-type graphs. Zhu, L.; Ghasemi-Gol, M.; Szekely, P.; Galstyan, A.; and Knoblock, C. A In International semantic web conference, pages 649–667, 2016. Springer, Cham
link bibtex 31 downloads

@inproceedings{zhu2016unsupervised,
  title={Unsupervised entity resolution on multi-type graphs},
  author={Zhu, Linhong and Ghasemi-Gol, Majid and Szekely, Pedro and Galstyan, Aram and Knoblock, Craig A},
  booktitle={International semantic web conference},
  pages={649--667},
  year={2016},
  organization={Springer, Cham}
}

Sifting common information from many variables. Steeg, G. V.; Gao, S.; Reing, K.; and Galstyan, A. arXiv preprint arXiv:1606.02307. 2016.
link bibtex

@article{steeg2016sifting,
  title={Sifting common information from many variables},
  author={Steeg, Greg Ver and Gao, Shuyang and Reing, Kyle and Galstyan, Aram},
  journal={arXiv preprint arXiv:1606.02307},
  year={2016}
}

Inferring Structure and Forecasting Dynamics on Evolving Networks. Brantingham, J. P; Breiger, R.; Chang, Y.; Galstyan, A.; Lerman, K.; McBride, M.; Mezic, I.; Milward, B.; Morrison, C.; Percus, A.; and others Technical Report UCLA Office of Contract and Grant Administration Los Angeles United States, 2016.
link bibtex

@techreport{brantingham2016inferring,
  title={Inferring Structure and Forecasting Dynamics on Evolving Networks},
  author={Brantingham, Jeffrey P and Breiger, Ronald and Chang, Yu-han and Galstyan, Aram and Lerman, Kristina and McBride, Michael and Mezic, Igor and Milward, Brinton and Morrison, Clayton and Percus, Allon and others},
  year={2016},
  institution={UCLA Office of Contract and Grant Administration Los Angeles United States}
}

Variational information maximization for feature selection. Gao, S.; Ver Steeg, G.; and Galstyan, A. Advances in neural information processing systems, 29. 2016.
link bibtex

@article{gao2016variational,
  title={Variational information maximization for feature selection},
  author={Gao, Shuyang and Ver Steeg, Greg and Galstyan, Aram},
  journal={Advances in neural information processing systems},
  volume={29},
  year={2016}
}

Situational Awareness for Social Media: Theories, Models and Algorithms. Galstyan, A.; Lerman, K.; Hovy, E.; Liu, Y.; and Nevatia, R. Technical Report University of Southern California Los Angeles United States, 2016.
link bibtex

@techreport{galstyan2016situational,
  title={Situational Awareness for Social Media: Theories, Models and Algorithms},
  author={Galstyan, Aram and Lerman, Kristina and Hovy, Eduard and Liu, Yan and Nevatia, Ram},
  year={2016},
  institution={University of Southern California Los Angeles United States}
}

Using Social Media, Online Social Networks and Internet Search As Platforms for Public Health Interventions. Huesch, M.; Galstyan, A.; Doctor, J.; and Ong, M. In 2016 Annual Research Meeting, 2016. AcademyHealth
link bibtex

@inproceedings{huesch2016using,
  title={Using Social Media, Online Social Networks and Internet Search As Platforms for Public Health Interventions},
  author={Huesch, Marco and Galstyan, Aram and Doctor, Jason and Ong, Michael},
  booktitle={2016 Annual Research Meeting},
  year={2016},
  organization={AcademyHealth}
}
%%2015

2015 (10)

Active inference for binary symmetric hidden Markov models. Allahverdyan, A. E; and Galstyan, A. Journal of Statistical Physics, 161(2): 452–466. 2015.
link bibtex

@article{allahverdyan2015active,
  title={Active inference for binary symmetric hidden Markov models},
  author={Allahverdyan, Armen E and Galstyan, Aram},
  journal={Journal of Statistical Physics},
  volume={161},
  number={2},
  pages={452--466},
  year={2015},
  publisher={Springer US}
}

Learning bounded rationality models of the adversary in repeated Stackelberg Security Games. Kar, D.; Fang, F.; Delle Fave, F.; Sintov, N.; Sinha, A.; Galstyan, A.; An, B.; and Tambe, M. Retrieved from Nanyang Technological University: http://www3. ntu. edu. sg/home/boan/papers/ALA15_Debarun. pdf. 2015.
link bibtex

@article{kar2015learning,
  title={Learning bounded rationality models of the adversary in repeated Stackelberg Security Games},
  author={Kar, Debarun and Fang, Fei and Delle Fave, Francesco and Sintov, Nicole and Sinha, Arunesh and Galstyan, Aram and An, Bo and Tambe, Milind},
  journal={Retrieved from Nanyang Technological University: http://www3. ntu. edu. sg/home/boan/papers/ALA15\_Debarun. pdf},
  year={2015}
}

Predicting Cognitive Decline with Information-Theoretic Clustering of Brain MRI and Blood Tests. Madsen, S. K; Ver Steeg, G.; Mezher, A.; Jahanshad, N.; Nir, T. M; Hua, X.; Gutman, B. A; Galstyan, A.; and Thompson, P. M In BIOLOGICAL PSYCHIATRY, volume 77, pages 96S–96S, 2015. ELSEVIER SCIENCE INC
link bibtex

@inproceedings{madsen2015predicting,
  title={Predicting Cognitive Decline with Information-Theoretic Clustering of Brain MRI and Blood Tests},
  author={Madsen, Sarah K and Ver Steeg, Greg and Mezher, Adam and Jahanshad, Neda and Nir, Talia M and Hua, Xue and Gutman, Boris A and Galstyan, Aram and Thompson, Paul M},
  booktitle={BIOLOGICAL PSYCHIATRY},
  volume={77},
  number={9},
  pages={96S--96S},
  year={2015},
  organization={ELSEVIER SCIENCE INC}
}

Information-theoretic characterization of blood panel predictors for brain atrophy and cognitive decline in the elderly. Madsen, S. K; Ver Steeg, G.; Mezher, A.; Jahanshad, N.; Nir, T. M; Hua, X.; Gutman, B. A; Galstyan, A.; and Thompson, P. M In 2015 IEEE 12th International Symposium on Biomedical Imaging (ISBI), pages 980–984, 2015. IEEE
link bibtex

@inproceedings{madsen2015information,
  title={Information-theoretic characterization of blood panel predictors for brain atrophy and cognitive decline in the elderly},
  author={Madsen, Sarah K and Ver Steeg, Greg and Mezher, Adam and Jahanshad, Neda and Nir, Talia M and Hua, Xue and Gutman, Boris A and Galstyan, Aram and Thompson, Paul M},
  booktitle={2015 IEEE 12th International Symposium on Biomedical Imaging (ISBI)},
  pages={980--984},
  year={2015},
  organization={IEEE}
}

Using Online Social Media and Social Networks as a Public Health Intervention. Huesch, M.; Doctor, J. N; and Galstyan, A. CESR-Schaeffer Working Paper, (2015-011). 2015.
link bibtex

@article{huesch2015using,
  title={Using Online Social Media and Social Networks as a Public Health Intervention},
  author={Huesch, Marco and Doctor, Jason N and Galstyan, Aram},
  journal={CESR-Schaeffer Working Paper},
  number={2015-011},
  year={2015}
}

Estimating Mutual Information by Local Gaussian Approximation. Gao, S.; Steeg, G. V.; and Galstyan, A. In Proceedings of the Thirty-First Conference on Uncertainty in Artificial Intelligence, of UAI'15, pages 278–287, Arlington, Virginia, USA, 2015. AUAI Press
link bibtex

@inproceedings{gao2015estimating,
    author = {Gao, Shuyang and Steeg, Greg Ver and Galstyan, Aram},
    title = {Estimating Mutual Information by Local Gaussian Approximation},
    year = {2015},
    isbn = {9780996643108},
    publisher = {AUAI Press},
    address = {Arlington, Virginia, USA},
     booktitle = {Proceedings of the Thirty-First Conference on Uncertainty in Artificial Intelligence},
    pages = {278–287},
    numpages = {10},
    location = {Amsterdam, Netherlands},
    series = {UAI'15}
    }

Memory-induced mechanism for self-sustaining activity in networks. Allahverdyan, A. E; Ver Steeg, G.; and Galstyan, A. Physical Review E, 92(6): 062824. 2015.
link bibtex

@article{allahverdyan2015memory,
  title={Memory-induced mechanism for self-sustaining activity in networks},
  author={Allahverdyan, Armen E and Ver Steeg, Greg and Galstyan, Aram},
  journal={Physical Review E},
  volume={92},
  number={6},
  pages={062824},
  year={2015},
  publisher={American Physical Society}
}

Information-theoretic clustering of neuroimaging metrics related to cognitive decline in the elderly. Daianu, M.; Steeg, G. V.; Mezher, A.; Jahanshad, N.; Nir, T. M; Yan, X.; Prasad, G.; Lerman, K.; Galstyan, A.; and Thompson, P. M In International MICCAI Workshop on Medical Computer Vision, pages 13–23, 2015. Springer, Cham
link bibtex

@inproceedings{daianu2015information,
  title={Information-theoretic clustering of neuroimaging metrics related to cognitive decline in the elderly},
  author={Daianu, Madelaine and Steeg, Greg Ver and Mezher, Adam and Jahanshad, Neda and Nir, Talia M and Yan, Xiaoran and Prasad, Gautam and Lerman, Kristina and Galstyan, Aram and Thompson, Paul M},
  booktitle={International MICCAI Workshop on Medical Computer Vision},
  pages={13--23},
  year={2015},
  organization={Springer, Cham}
}

Outreach Using Social Media Campaigns: Micro-Education for $1 per Patient. Huesch, M.; Doctor, J.; and Galstyan, A. In 2015 Annual Research Meeting, 2015. AcademyHealth
link bibtex

@inproceedings{huesch2015outreach,
  title={Outreach Using Social Media Campaigns: Micro-Education for $1 per Patient},
  author={Huesch, Marco and Doctor, Jason and Galstyan, Aram},
  booktitle={2015 Annual Research Meeting},
  year={2015},
  organization={AcademyHealth}
}

Efficient estimation of mutual information for strongly dependent variables. Gao, S.; Ver Steeg, G.; and Galstyan, A. In Artificial intelligence and statistics, pages 277–286, 2015. PMLR
link bibtex

@inproceedings{gao2015efficient,
  title={Efficient estimation of mutual information for strongly dependent variables},
  author={Gao, Shuyang and Ver Steeg, Greg and Galstyan, Aram},
  booktitle={Artificial intelligence and statistics},
  pages={277--286},
  year={2015},
  organization={PMLR}
}
%%2014

2014 (9)

Modeling temporal activity patterns in dynamic social networks. Raghavan, V.; Ver Steeg, G.; Galstyan, A.; and Tartakovsky, A. G IEEE Transactions on Computational Social Systems, 1(1): 89–107. 2014.
link bibtex

@article{raghavan2014modeling,
  title={Modeling temporal activity patterns in dynamic social networks},
  author={Raghavan, Vasanthan and Ver Steeg, Greg and Galstyan, Aram and Tartakovsky, Alexander G},
  journal={IEEE Transactions on Computational Social Systems},
  volume={1},
  number={1},
  pages={89--107},
  year={2014},
  publisher={IEEE}
}

Phase transitions in community detection: A solvable toy model. Ver Steeg, G.; Moore, C.; Galstyan, A.; and Allahverdyan, A. EPL (Europhysics Letters), 106(4): 48004. 2014.
link bibtex 22 downloads

@article{ver2014phase,
  title={Phase transitions in community detection: A solvable toy model},
  author={Ver Steeg, Greg and Moore, Cristopher and Galstyan, Aram and Allahverdyan, Armen},
  journal={EPL (Europhysics Letters)},
  volume={106},
  number={4},
  pages={48004},
  year={2014},
  publisher={IOP Publishing}
}

Tripartite graph clustering for dynamic sentiment analysis on social media. Zhu, L.; Galstyan, A.; Cheng, J.; and Lerman, K. In Proceedings of the 2014 ACM SIGMOD international conference on Management of data, pages 1531–1542, 2014.
link bibtex 43 downloads

@inproceedings{zhu2014tripartite,
  title={Tripartite graph clustering for dynamic sentiment analysis on social media},
  author={Zhu, Linhong and Galstyan, Aram and Cheng, James and Lerman, Kristina},
  booktitle={Proceedings of the 2014 ACM SIGMOD international conference on Management of data},
  pages={1531--1542},
  year={2014}
}

Where and why users “check in”. Cho, Y.; Ver Steeg, G.; and Galstyan, A. In Proc. of AAAI, volume 14, pages 269–275, 2014.
link bibtex 40 downloads

@inproceedings{cho2014and,
  title={Where and why users “check in”},
  author={Cho, Yoon-Sik and Ver Steeg, Greg and Galstyan, Aram},
  booktitle={Proc. of AAAI},
  volume={14},
  pages={269--275},
  year={2014}
}

Discovering structure in high-dimensional data through correlation explanation. Ver Steeg, G.; and Galstyan, A. Advances in Neural Information Processing Systems, 27. 2014.
link bibtex

@article{ver2014discovering,
  title={Discovering structure in high-dimensional data through correlation explanation},
  author={Ver Steeg, Greg and Galstyan, Aram},
  journal={Advances in Neural Information Processing Systems},
  volume={27},
  year={2014}
}

Opinion dynamics with confirmation bias. Allahverdyan, A. E; and Galstyan, A. PloS one, 9(7): e99557. 2014.
link bibtex

@article{allahverdyan2014opinion,
  title={Opinion dynamics with confirmation bias},
  author={Allahverdyan, Armen E and Galstyan, Aram},
  journal={PloS one},
  volume={9},
  number={7},
  pages={e99557},
  year={2014},
  publisher={Public Library of Science}
}

Mixed Membership Blockmodels for Dynamic Networks with Feedback. Cho, Y.; Ver Steeg, G.; and Galstyan, A. 2014.
link bibtex

@misc{cho2014mixed,
  title={Mixed Membership Blockmodels for Dynamic Networks with Feedback.},
  author={Cho, Yoon-Sik and Ver Steeg, Greg and Galstyan, Aram},
  year={2014}
}

Maximally Informative Hierarchical Representations of High-Dimensional Data. Ver Steeg, G.; and Galstyan, A. In Artificial Intelligence and Statistics (AISTATS), 2014.
link bibtex

@inproceedings{ver2014maximally,
  title={Maximally Informative Hierarchical Representations of High-Dimensional Data},
  author={Ver Steeg, Greg and Galstyan, Aram},
  booktitle={Artificial Intelligence and Statistics (AISTATS)},
  year={2014}
}

Understanding confounding effects in linguistic coordination: an information-theoretic approach. Gao, S.; Ver Steeg, G.; and Galstyan, A. arXiv preprint arXiv:1412.0696. 2014.
link bibtex

@article{gao2014understanding,
  title={Understanding confounding effects in linguistic coordination: an information-theoretic approach},
  author={Gao, Shuyang and Ver Steeg, Greg and Galstyan, Aram},
  journal={arXiv preprint arXiv:1412.0696},
  year={2014}
}
%%2013

2013 (10)

Continuous strategy replicator dynamics for multi-agent q-learning. Galstyan, A. Autonomous agents and multi-agent systems, 26(1): 37–53. 2013.
link bibtex

@article{galstyan2013continuous,
  title={Continuous strategy replicator dynamics for multi-agent q-learning},
  author={Galstyan, Aram},
  journal={Autonomous agents and multi-agent systems},
  volume={26},
  number={1},
  pages={37--53},
  year={2013},
  publisher={Springer US}
}

Hidden Markov models for the activity profile of terrorist groups. Raghavan, V.; Galstyan, A.; and Tartakovsky, A. G The Annals of Applied Statistics,2402–2430. 2013.
link bibtex

@article{raghavan2013hidden,
  title={Hidden Markov models for the activity profile of terrorist groups},
  author={Raghavan, Vasanthan and Galstyan, Aram and Tartakovsky, Alexander G},
  journal={The Annals of Applied Statistics},
  pages={2402--2430},
  year={2013},
  publisher={Institute of Mathematical Statistics}
}

Sentiment prediction using collaborative filtering. Kim, J.; Yoo, J.; Lim, H.; Qiu, H.; Kozareva, Z.; and Galstyan, A. In Proceedings of the International AAAI Conference on Web and Social Media, volume 7, pages 685–688, 2013.
link bibtex 6 downloads

@inproceedings{kim2013sentiment,
  title={Sentiment prediction using collaborative filtering},
  author={Kim, Jihie and Yoo, Jaebong and Lim, Ho and Qiu, Huida and Kozareva, Zornitsa and Galstyan, Aram},
  booktitle={Proceedings of the International AAAI Conference on Web and Social Media},
  volume={7},
  number={1},
  pages={685--688},
  year={2013}
}

Vaccination (anti-) campaigns in social media. Huesch, M.; Ver Steeg, G.; and Galstyan, A. In Workshops at the Twenty-Seventh AAAI Conference on Artificial Intelligence, 2013.
link bibtex

@inproceedings{huesch2013vaccination,
  title={Vaccination (anti-) campaigns in social media},
  author={Huesch, Marco and Ver Steeg, Greg and Galstyan, Aram},
  booktitle={Workshops at the Twenty-Seventh AAAI Conference on Artificial Intelligence},
  year={2013}
}

Socially relevant venue clustering from check-in data. Cho, Y.; Ver Steeg, G.; and Galstyan, A. In KDD Workshop on Mining and Learning with Graphs, 2013.
link bibtex

@inproceedings{cho2013socially,
  title={Socially relevant venue clustering from check-in data},
  author={Cho, Yoon-Sik and Ver Steeg, Greg and Galstyan, Aram},
  booktitle={KDD Workshop on Mining and Learning with Graphs},
  year={2013}
}

Coevolutionary networks of reinforcement-learning agents. Kianercy, A.; and Galstyan, A. Physical Review E, 88(1): 012815. 2013.
link bibtex 6 downloads

@article{kianercy2013coevolutionary,
  title={Coevolutionary networks of reinforcement-learning agents},
  author={Kianercy, Ardeshir and Galstyan, Aram},
  journal={Physical Review E},
  volume={88},
  number={1},
  pages={012815},
  year={2013},
  publisher={American Physical Society}
}

Coupled hidden markov models for user activity in social networks. Raghavan, V.; Ver Steeg, G.; Galstyan, A.; and Tartakovsky, A. G In 2013 IEEE International Conference on Multimedia and Expo Workshops (ICMEW), pages 1–6, 2013. IEEE
link bibtex

@inproceedings{raghavan2013coupled,
  title={Coupled hidden markov models for user activity in social networks},
  author={Raghavan, Vasanthan and Ver Steeg, Greg and Galstyan, Aram and Tartakovsky, Alexander G},
  booktitle={2013 IEEE International Conference on Multimedia and Expo Workshops (ICMEW)},
  pages={1--6},
  year={2013},
  organization={IEEE}
}

Demystifying information-theoretic clustering. Ver Steeg, G.; Galstyan, A.; Sha, F.; and DeDeo, S. In ICML, 2013.
link bibtex

@inproceedings{ver2013demystifying,
  title={Demystifying information-theoretic clustering},
  author={Ver Steeg, Greg and Galstyan, Aram and Sha, Fei and DeDeo, Simon},
  booktitle={ICML},
  year={2013}
}

Activation Cascades in Structured Populations. Galstyan, A. In Handbook of Human Computation, pages 779–789. Springer, New York, NY, 2013.
link bibtex

@incollection{galstyan2013activation,
  title={Activation Cascades in Structured Populations},
  author={Galstyan, Aram},
  booktitle={Handbook of Human Computation},
  pages={779--789},
  year={2013},
  publisher={Springer, New York, NY}
}

Latent self-exciting point process model for spatial-temporal networks. Cho, Y.; Galstyan, A.; Brantingham, P J.; and Tita, G. arXiv preprint arXiv:1302.2671. 2013.
link bibtex

@article{cho2013latent,
  title={Latent self-exciting point process model for spatial-temporal networks},
  author={Cho, Yoon-Sik and Galstyan, Aram and Brantingham, P Jeffrey and Tita, George},
  journal={arXiv preprint arXiv:1302.2671},
  year={2013}
}

%2012

2012 (5)

Adaptive agents on evolving networks. Kianercy, A.; Galstyan, A.; and Allahverdyan, A. E In AAMAS, pages 1391–1392, 2012.
link bibtex 4 downloads

@inproceedings{kianercy2012adaptive,
  title={Adaptive agents on evolving networks.},
  author={Kianercy, Ardeshir and Galstyan, Aram and Allahverdyan, Armen E},
  booktitle={AAMAS},
  pages={1391--1392},
  year={2012}
}

Dynamics of Boltzmann Q learning in two-player two-action games. Kianercy, A.; and Galstyan, A. Physical Review E, 85(4): 041145. 2012.
link bibtex 5 downloads

@article{kianercy2012dynamics,
  title={Dynamics of Boltzmann Q learning in two-player two-action games},
  author={Kianercy, Ardeshir and Galstyan, Aram},
  journal={Physical Review E},
  volume={85},
  number={4},
  pages={041145},
  year={2012},
  publisher={American Physical Society}
}

Generative models for spatial-temporal processes with applications to predictive criminology. Cho, Y; Galstyan, A.; Brantingham, J.; and Tita, G. . 2012.
link bibtex

@article{cho2012generative,
  title={Generative models for spatial-temporal processes with applications to predictive criminology},
  author={Cho, Y and Galstyan, Aram and Brantingham, Jeff and Tita, George},
  year={2012}
}

Information-Theoretic Measures of Influence Based on Content Dynamics. Steeg, G. V.; and Galstyan, A. arXiv preprint arXiv:1208.4475. 2012.
link bibtex 7 downloads

@article{steeg2012information,
  title={Information-Theoretic Measures of Influence Based on Content Dynamics},
  author={Steeg, Greg Ver and Galstyan, Aram},
  journal={arXiv preprint arXiv:1208.4475},
  year={2012}
}

Statistical tests for contagion in observational social network studies. Ver Steeg, G.; and Galstyan, A. arXiv preprint arXiv:1211.4889. 2012.
link bibtex

@article{ver2012statistical,
  title={Statistical tests for contagion in observational social network studies},
  author={Ver Steeg, Greg and Galstyan, Aram},
  journal={arXiv preprint arXiv:1211.4889},
  year={2012}
}
%%2011

2011 (9)

Information Transfer in Social Media. Ver Steeg, G.; and Galstyan, A. . 2011.
link bibtex 1 download

@article{ver2011information,
  title={Information Transfer in Social Media},
  author={Ver Steeg, Greg and Galstyan, Aram},
  year={2011}
}

Co-evolution of selection and influence in social networks. Cho, Y.; Ver Steeg, G.; and Galstyan, A. arXiv preprint arXiv:1106.2788. 2011.
link bibtex 15 downloads

@article{cho2011co,
  title={Co-evolution of selection and influence in social networks},
  author={Cho, Yoon-Sik and Ver Steeg, Greg and Galstyan, Aram},
  journal={arXiv preprint arXiv:1106.2788},
  year={2011}
}

Social mechanics: An empirically grounded science of social media. Lerman, K.; Galstyan, A.; Ver Steeg, G.; and Hogg, T. In Proceedings of the International AAAI Conference on Web and Social Media, volume 5, pages 13–22, 2011.
link bibtex

@inproceedings{lerman2011social,
  title={Social mechanics: An empirically grounded science of social media},
  author={Lerman, Kristina and Galstyan, Aram and Ver Steeg, Greg and Hogg, Tad},
  booktitle={Proceedings of the International AAAI Conference on Web and Social Media},
  volume={5},
  number={4},
  pages={13--22},
  year={2011}
}

Comparative Analysis of Viterbi Training and Maximum Likelihood Estimation for HMMs. Allahverdyan, A.; and Galstyan, A. In Neural Information Processing Systems (NIPS)., 2011.
link bibtex

@inproceedings{allahverdyan2011comparative,
  title={Comparative Analysis of Viterbi Training and Maximum Likelihood Estimation for HMMs},
  author={Allahverdyan, Armen and Galstyan, Aram},
  booktitle={Neural Information Processing Systems (NIPS).},
  year={2011}
}

A Sequence of Relaxations Constraining Hidden Variable Models. Ver Steeg, G.; and Galstyan, A. . 2011.
link bibtex 5 downloads

@article{ver2011sequence,
  title={A Sequence of Relaxations Constraining Hidden Variable Models},
  author={Ver Steeg, Greg and Galstyan, Aram},
  year={2011}
}

Statistical mechanics of semi-supervised clustering in sparse graphs. Ver Steeg, G.; Galstyan, A.; and Allahverdyan, A. E Journal of Statistical Mechanics: Theory and Experiment, 2011(08): P08009. 2011.
link bibtex 3 downloads

@article{ver2011statistical,
  title={Statistical mechanics of semi-supervised clustering in sparse graphs},
  author={Ver Steeg, Greg and Galstyan, Aram and Allahverdyan, Armen E},
  journal={Journal of Statistical Mechanics: Theory and Experiment},
  volume={2011},
  number={08},
  pages={P08009},
  year={2011},
  publisher={IOP Publishing}
}

Le Chatelier's principle in replicator dynamics. Allahverdyan, A. E; and Galstyan, A. Physical Review E, 84(4): 041117. 2011.
link bibtex

@article{allahverdyan2011chatelier,
  title={Le Chatelier's principle in replicator dynamics},
  author={Allahverdyan, Armen E and Galstyan, Aram},
  journal={Physical Review E},
  volume={84},
  number={4},
  pages={041117},
  year={2011},
  publisher={APS}
}

Spatio-Temporal Nonlinear Filtering With Applications to Information Assurance and Counter Terrorism. Rozovsky, B.; Tartakovsky, A.; Bertozzi, A; Galstyan, A; Medioni, G; Papadopoulos, C; and Veeravalli, V Technical Report BROWN UNIV PROVIDENCE RI DIV OF APPLIED MATHEMATICS, 2011.
link bibtex

@techreport{rozovsky2011spatio,
  title={Spatio-Temporal Nonlinear Filtering With Applications to Information Assurance and Counter Terrorism},
  author={Rozovsky, Boris and Tartakovsky, Alexander and Bertozzi, A and Galstyan, A and Medioni, G and Papadopoulos, C and Veeravalli, V},
  year={2011},
  institution={BROWN UNIV PROVIDENCE RI DIV OF APPLIED MATHEMATICS}
}

Stochastic models of social media dynamics. Lerman, K.; Galstyan, A.; Ver Steeg, G.; and Hogg, T. In 5th International AAAI Conference on Weblogs and Social Media (ICWSM), Barcelona, Spain, 2011.
link bibtex

@inproceedings{lerman2011stochastic,
  title={Stochastic models of social media dynamics},
  author={Lerman, Kristina and Galstyan, Aram and Ver Steeg, Greg and Hogg, Tad},
  booktitle={5th International AAAI Conference on Weblogs and Social Media (ICWSM), Barcelona, Spain},
  year={2011}
}
%%2010

2010 (4)

Towards modeling social and content dynamics in discussion forums. Kim, J.; and Galstyan, A. In Proceedings of the NAACL HLT 2010 Workshop on Computational Linguistics in a World of Social Media, pages 13–14, 2010.
link bibtex

@inproceedings{kim2010towards,
  title={Towards modeling social and content dynamics in discussion forums},
  author={Kim, Jihie and Galstyan, Aram},
  booktitle={Proceedings of the NAACL HLT 2010 Workshop on Computational Linguistics in a World of Social Media},
  pages={13--14},
  year={2010}
}

Replicator Dynamics of Coevolving Networks. Galstyan, A.; Kianercy, A.; and Allahverdyan, A. In 2010 AAAI Fall Symposium Series, 2010.
link bibtex 1 download

@inproceedings{galstyan2010replicator,
  title={Replicator Dynamics of Coevolving Networks},
  author={Galstyan, Aram and Kianercy, Ardeshir and Allahverdyan, Armen},
  booktitle={2010 AAAI Fall Symposium Series},
  year={2010}
}

Ruling out latent homophily in social networks. Ver Steeg, G.; and Galstyan, A. NIPSWorkshop on Social Computing. 2010.
link bibtex

@article{ver2010ruling,
  title={Ruling out latent homophily in social networks},
  author={Ver Steeg, Greg and Galstyan, Aram},
  journal={NIPSWorkshop on Social Computing},
  year={2010}
}

Community detection with and without prior information. Allahverdyan, A. E; Ver Steeg, G.; and Galstyan, A. EPL (Europhysics Letters), 90(1): 18002. 2010.
link bibtex 3 downloads

@article{allahverdyan2010community,
  title={Community detection with and without prior information},
  author={Allahverdyan, Armen E and Ver Steeg, Greg and Galstyan, Aram},
  journal={EPL (Europhysics Letters)},
  volume={90},
  number={1},
  pages={18002},
  year={2010},
  publisher={IOP Publishing}
}

%%2009

2009 (3)

Maximizing influence propagation in networks with community structure. Galstyan, A.; Musoyan, V.; and Cohen, P. Physical Review E, 79(5): 056102. 2009.
link bibtex 1 download

@article{galstyan2009maximizing,
  title={Maximizing influence propagation in networks with community structure},
  author={Galstyan, Aram and Musoyan, Vahe and Cohen, Paul},
  journal={Physical Review E},
  volume={79},
  number={5},
  pages={056102},
  year={2009},
  publisher={APS}
}

Tentacles: Self-configuring robotic radio networks in unknown environments. Chiu, H. C. H.; Ryu, B.; Zhu, H.; Szekely, P.; Maheswaran, R.; Rogers, C.; Galstyan, A.; Salemi, B.; Rubenstein, M.; and Shen, W. In 2009 IEEE/RSJ International Conference on Intelligent Robots and Systems, pages 1383–1388, 2009. IEEE
link bibtex

@inproceedings{chiu2009tentacles,
  title={Tentacles: Self-configuring robotic radio networks in unknown environments},
  author={Chiu, Harris Chi Ho and Ryu, Bo and Zhu, Hua and Szekely, Pedro and Maheswaran, Rajiv and Rogers, Craig and Galstyan, Aram and Salemi, Behnam and Rubenstein, Mike and Shen, Wei-Min},
  booktitle={2009 IEEE/RSJ International Conference on Intelligent Robots and Systems},
  pages={1383--1388},
  year={2009},
  organization={IEEE}
}

On maximum a posteriori estimation of hidden Markov processes. Allahverdyan, A.; and Galstyan, A. arXiv preprint arXiv:0906.1980. 2009.
link bibtex 5 downloads

@article{allahverdyan2009maximum,
  title={On maximum a posteriori estimation of hidden Markov processes},
  author={Allahverdyan, Armen and Galstyan, Aram},
  journal={arXiv preprint arXiv:0906.1980},
  year={2009}
}
%%2008

2008 (4)

Influence Propagation in Modular Networks. Galstyan, A.; and Cohen, P. R In AAAI Spring Symposium: Social Information Processing, pages 21–23, 2008.
link bibtex

@inproceedings{galstyan2008influence,
  title={Influence Propagation in Modular Networks.},
  author={Galstyan, Aram and Cohen, Paul R},
  booktitle={AAAI Spring Symposium: Social Information Processing},
  pages={21--23},
  year={2008}
}

Comparing Diffusion Models for Graph–Based Semi–Supervised Learning. Galstyan, A.; and Cohen, P. R In 6th International Workshop on Mining and Learning with Graphs, 2008.
link bibtex

@inproceedings{galstyan2008comparing,
  title={Comparing Diffusion Models for Graph--Based Semi--Supervised Learning},
  author={Galstyan, Aram and Cohen, Paul R},
  booktitle={6th International Workshop on Mining and Learning with Graphs},
  year={2008}
}

Analysis of social voting patterns on digg. Lerman, K.; and Galstyan, A. In Proceedings of the first workshop on Online social networks, pages 7–12, 2008.
link bibtex 4 downloads

@inproceedings{lerman2008analysis,
  title={Analysis of social voting patterns on digg},
  author={Lerman, Kristina and Galstyan, Aram},
  booktitle={Proceedings of the first workshop on Online social networks},
  pages={7--12},
  year={2008}
}

Top-down vs bottom-up methodologies in multi-agent system design. Crespi, V.; Galstyan, A.; and Lerman, K. Autonomous Robots, 24(3): 303–313. 2008.
link bibtex

@article{crespi2008top,
  title={Top-down vs bottom-up methodologies in multi-agent system design},
  author={Crespi, Valentino and Galstyan, Aram and Lerman, Kristina},
  journal={Autonomous Robots},
  volume={24},
  number={3},
  pages={303--313},
  year={2008},
  publisher={Springer US}
}
%%2007

2007 (2)

Cascading dynamics in modular networks. Galstyan, A.; and Cohen, P. Physical Review E, 75(3): 036109. 2007.
link bibtex 5 downloads

@article{galstyan2007cascading,
  title={Cascading dynamics in modular networks},
  author={Galstyan, Aram and Cohen, Paul},
  journal={Physical Review E},
  volume={75},
  number={3},
  pages={036109},
  year={2007},
  publisher={American Physical Society}
}

Empirical comparison of “hard” and “soft” label propagation for relational classification. Galstyan, A.; and Cohen, P. R In International Conference on Inductive Logic Programming, pages 98–111, 2007. Springer, Berlin, Heidelberg
link bibtex

@inproceedings{galstyan2007empirical,
  title={Empirical comparison of “hard” and “soft” label propagation for relational classification},
  author={Galstyan, Aram and Cohen, Paul R},
  booktitle={International Conference on Inductive Logic Programming},
  pages={98--111},
  year={2007},
  organization={Springer, Berlin, Heidelberg}
}