2015+ Papers

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  • Minimax-Regret Querying on Side Effects for Safe Optimality in Factored Markov Decision Processes
    by Shun Zhang, Edmund Durfee, and Satinder Singh.
    In International Joint Conference on Artificial Intelligence (IJCAI), 2018.
    pdf.

  • Markov Decision Processes with Continuous Side Information
    by Aditya Modi, Nan Jiang, Satinder Singh, and Ambuj Tewari.
    In International Conference on Algorithmic Learning Theory (ALT), 2018.
    conf pdf, arXiv link.

  • Value Prediction Networks
    by Junhyuk Oh, Satinder Singh, Honglak Lee.
    In Neural Information Processing Systems (NIPS), 2017.
    arXiv link.

  • Repeated Inverse Reinforcement Learning
    by Kareem Amin, Nan Jiang, and Satinder Singh.
    In Neural Information Processing Systems (NIPS), 2017.
    arXiv link.

  • A Big Step for AI
    by Satinder Singh.
    In Nature: News & Views, 2017.
    pdf.

  • Zero-Shot Task Generalization with Multi-Task Deep Reinforcement Learning
    by Junhyuk Oh, Satinder Singh, Honglak Lee, and Pushmeet Kohli.
    In International Conference on Machine Learning (ICML), 2017.
    pdf.

  • A Stackelberg Game Model for Botnet Data Exfiltration
    by Thang Nguyen, Michael Wellman, and Satinder Singh.
    In Proceedings of the 8th Conference on Decision and Game Theory for Security (GameSec), 2017.
    pdf.

  • Learning to Query, Reason, and Answer Questions on Ambiguous Texts.
    by Xiaoxiao Guo, Tim Klinger, Clemens Rosenbaum, Jospeh Bigus, Murray Campbell, Ban Kawas, Kartik Talamadupula, Gerald Tesauro, and Satinder Singh.
    In 5th International Conference on Learning Representations (ICLR), 2017.
    pdf.

  • Approximately-Optimal Queries for Planning in Reward-Uncertain Markov Decision Processes.
    by Shun Zhang, Edmund Durfee, and Satinder Singh.
    In 27th International Conference on Automated Planning and Scheduling (ICAPS), 2017.
    pdf.

  • Minimizing Maximum Regret in Commitment Constrained Sequential Decision Making.
    by Qi Zhang, Satinder Singh, and Edmund Durfee.
    In 27th International Conference on Automated Planning and Scheduling (ICAPS), 2017.
    pdf.

  • Predicting Counselor Behaviors in Motivational Interviewing Encounters.
    by Veronica Perez-Rosas, Rada Mihalcea, Kenneth Resnicow, Satinder Singh, Lawrence An, Kathy J. Goggin, and Delwyn Catley.
    In Proceedings of the European Association of Computational Linguistics, (EACL) 2017.
    pdf.

  • Control of Memory, Active Perception, and Action in Minecraft.
    by Junhyuk Oh, Valliappa Chockalingum, Satinder Singh, and Honglak Lee.
    In 33rd International Conference on Machine Learning (ICML), 2016.
    pdf.

  • Gradient Methods for Stackelberg Security Games.
    by Kareem Amin, Satinder Singh, and Michael Wellman.
    In Conference on Uncertainty in Artificial Intelligence (UAI), 2016.
    pdf.

  • Deep Learning for Reward Design to Improve Monte Carlo Tree Search in ATARI Games.
    by Xiaoxiao Guo, Satinder Singh, Richard Lewis, and Honglak Lee.
    In 25th International Joint Conference on Artificial Intelligence (IJCAI), 2016.
    pdf.

  • Commitment Semantics for Sequential Decision Making Under Reward Uncertainty.
    by Qi Zhang, Edmund Durfee, Satinder Singh, Anna Chen, and Stefan Witwicki.
    In 25th International Joint Conference on Artificial Intelligence (IJCAI), 2016.
    pdf.

  • On Structural Properties of MDPs that Bound Loss Due to Shallow Planning.
    by Nan Jiang, Satinder Singh and Ambuj Tewari.
    In 25th International Joint Conference on Artificial Intelligence (IJCAI), 2016.
    pdf.

  • On the Trustworthy Fulfillment of Commitments.
    by Edmund Durfee and Satinder Singh.
    In Proceedings of the 18th International Workshop on Trust in Agent Societies (TRUST), 2016.
    pdf.

  • Building a Motivational Interviewing Dataset.
    by Veronica Perez-Rosas, Rada Mihalcea, Kenneth Resnicow, Lawrence An, and Satinder Singh.
    In Proceedings of the NAACL 2016 Workshop on Clinical Psychology, 2016.
    pdf.

  • Patient-Centerd Pain Care Using Artificial Intelligence and Mobile Health Tools: Protocol for a Randomized Study Funded by the US Department of Veterans Affairs Health Services Research and Development Program.
    by Piette JD, Krein SL, Striplin D, Marinec N, Kerns RD, Farris KB, Singh S, An L, and Heapy AA.
    In JMIR Research Protocols; 5(2) 2016.
    pdf.

  • Improving Predictive State Representations via Gradient Descent.
    by Nan Jiang, Alex Kulesza, and Satinder Singh.
    In Thirtieth AAAI Conference on Artificial Intelligence (AAAI), 2016.
    pdf.

  • Confirming the theoretical structure of expert-developed text messages to improve adherence to anti-hypertensive medications.
    by Karen Farris, Teresa Salgado, Peter Batra, John Piette, Satinder Singh, Ahmed Guhad, Sean Newman, Vincent Marshall, and Larry An.
    In Research in Social and Administrative Pharmacy, 2015.
    pdf.

  • Action-Conditional Video Prediction Using Deep Networks in ATARI Games.
    by Juhnyuk Oh, Xiaoxiao Guo, Honglak Lee, Richard Lewis, and Satinder Singh.
    In Neural Information Processing Systems, 2015.
    online videos
    arxiv pdf, NIPS pdf, NIPS Appendix pdf.

  • Multi-Task Seizure Detection: Addressing Inter-Patient and Intra-Patient Variations in Seizure Morphologies.
    by Alex Van Esbroeck, Landon Smith, Zeeshan Syed, Satinder Singh, and Zahi Karam.
    In Machine Learning, 2015.
    pdf.

  • Abstraction Selection in Model-Based Reinforcement Learning.
    by Nan Jiang, Alex Kulesza, and Satinder Singh.
    In 32nd International Conference on Machine Learning (ICML), 2015.
    pdf.

  • The Dependence of Effective Planning Horizon on Model Accuracy.
    by Nan Jiang, Alex Kulesza, Satinder Singh, and Richard Lewis.
    In International Conference on Autonomous Agents and MultiAgent Systems (AAMAS), 2015.
    Best Paper Award
    pdf.

  • Low-Ranks Spectral Learning with Weighted Loss Functions.
    by Alex Kulesza, Nan Jiang, and Satinder Singh.
    In Eighteenth International Conference on Artificial Intelligence and Statistics (AISTATS), 2015.
    pdf.

  • Spectral Learning of Predictive State Representations with Insufficient Statistics.
    by Alex Kulesza, Nan Jiang, and Satinder Singh.
    In Twenty-Ninth AAAI Conference, 2015.
    pdf.

    All My Papers in Reverse Chronological Order