Satinder Singh
Publication record assembled from the DBLP archive of ranked conferences.
Papers indexed
108
Venues
27
Active years
1993–2025
Best venue rank
A*
Where they publish
- A*ICML24 papers
- A*AAAI23 papers
- A*IJCAI14 papers
- AUAI11 papers
- A*ICLR8 papers
- AAISTATS4 papers
- AAAMAS3 papers
- NationalISAIM2 papers
- AGECCO1 paper
- BGLOBECOM1 paper
- BIWCMC1 paper
- A*ICDM1 paper
- NationalRANLP1 paper
- BALT1 paper
- A*EMNLP1 paper
- A*ACL1 paper
- A*CCS1 paper
- AEACL1 paper
- ANAACL1 paper
- MulticonferenceICASSP1 paper
- NationalHCI1 paper
- A*SIGMOD1 paper
- CICMLA1 paper
- BCOLING1 paper
- A*COLT1 paper
- CRoboCup1 paper
- AUSENIX1 paper
Papers
108 indexed papers, newest first.
| Year | Venue | Title | Authors |
|---|---|---|---|
| 2025 | ICML | Mastering Board Games by External and Internal Planning with Language Models. | John Schultz, Jakub Admek, Matej Jusup, Marc Lanctot, Michael Kaisers, Sarah Perrin, Daniel Hennes, Jeremy Shar, Cannada A. Lewis, Anian Ruoss, Tom Zahavy, Petar Velickovic, Laurel Prince, Satinder Singh, Eric Malmi, Nenad Tomasev |
| 2024 | ICML | Genie: Generative Interactive Environments. | Jake Bruce, Michael D. Dennis, Ashley Edwards, Jack Parker-Holder, Yuge Shi, Edward Hughes, Matthew Lai, Aditi Mavalankar, Richie Steigerwald, Chris Apps, Yusuf Aytar, Sarah Bechtle, Feryal M. P. Behbahani, Stephanie C. Y. Chan, Nicolas Heess, Lucy Gonzalez, Simon Osindero, Sherjil Ozair, Scott E. Reed, Jingwei Zhang, Konrad Zolna, Jeff Clune, Nando de Freitas, Satinder Singh, Tim Rocktschel |
| 2023 | GECCO | Discovering Evolution Strategies via Meta-Black-Box Optimization. | Robert Tjarko Lange, Tom Schaul, Yutian Chen, Tom Zahavy, Valentin Dalibard, Chris Lu, Satinder Singh, Sebastian Flennerhag |
| 2023 | GLOBECOM | Jamming Mitigation for Mixed RF/FSO Relay Networks Under Simultaneous Interceptions. | Van Hau Le, Ti Ti Nguyen, Kim Khoa Nguyen, Verdier Assoume, Satinder Singh |
| 2023 | ICLR | Composing Task Knowledge With Modular Successor Feature Approximators. | Wilka Carvalho, Angelos Filos, Richard L. Lewis, Honglak Lee, Satinder Singh |
| 2023 | ICLR | Discovering Evolution Strategies via Meta-Black-Box Optimization. | Robert Tjarko Lange, Tom Schaul, Yutian Chen, Tom Zahavy, Valentin Dalibard, Chris Lu, Satinder Singh, Sebastian Flennerhag |
| 2023 | ICLR | In-context Reinforcement Learning with Algorithm Distillation. | Michael Laskin, Luyu Wang, Junhyuk Oh, Emilio Parisotto, Stephen Spencer, Richie Steigerwald, DJ Strouse, Steven Stenberg Hansen, Angelos Filos, Ethan Brooks, Maxime Gazeau, Himanshu Sahni, Satinder Singh, Volodymyr Mnih |
| 2023 | ICLR | Discovering Policies with DOMiNO: Diversity Optimization Maintaining Near Optimality. | Tom Zahavy, Yannick Schroecker, Feryal M. P. Behbahani, Kate Baumli, Sebastian Flennerhag, Shaobo Hou, Satinder Singh |
| 2023 | ICML | Human-Timescale Adaptation in an Open-Ended Task Space. | Jakob Bauer, Kate Baumli, Feryal M. P. Behbahani, Avishkar Bhoopchand, Nathalie Bradley-Schmieg, Michael Chang, Natalie Clay, Adrian Collister, Vibhavari Dasagi, Lucy Gonzalez, Karol Gregor, Edward Hughes, Sheleem Kashem, Maria Loks-Thompson, Hannah Openshaw, Jack Parker-Holder, Shreya Pathak, Nicolas Perez Nieves, Nemanja Rakicevic, Tim Rocktschel, Yannick Schroecker, Satinder Singh, Jakub Sygnowski, Karl Tuyls, Sarah York, Alexander Zacherl, Lei M. Zhang |
| 2023 | ICML | ReLOAD: Reinforcement Learning with Optimistic Ascent-Descent for Last-Iterate Convergence in Constrained MDPs. | Ted Moskovitz, Brendan O'Donoghue, Vivek Veeriah, Sebastian Flennerhag, Satinder Singh, Tom Zahavy |
| 2023 | IWCMC | Anti-jamming Transmission in NOMA-based Multi-cell Satellite-terrestrial Integrated Networks. | Chen Han, Haotong Cao, Zhi Lin, Kang An, Sahil Garg, Georges Kaddoum, Satinder Singh |
| 2022 | AAAI | Adaptive Pairwise Weights for Temporal Credit Assignment. | Zeyu Zheng, Risto Vuorio, Richard L. Lewis, Satinder Singh |
| 2022 | ICLR | Bootstrapped Meta-Learning. | Sebastian Flennerhag, Yannick Schroecker, Tom Zahavy, Hado van Hasselt, David Silver, Satinder Singh |
| 2022 | IJCAI | On the Expressivity of Markov Reward (Extended Abstract). | David Abel, Will Dabney, Anna Harutyunyan, Mark K. Ho, Michael L. Littman, Doina Precup, Satinder Singh |
| 2021 | AAAI | Efficient Querying for Cooperative Probabilistic Commitments. | Qi Zhang, Edmund H. Durfee, Satinder Singh |
| 2021 | ICLR | Discovering a set of policies for the worst case reward. | Tom Zahavy, Andr Barreto, Daniel J. Mankowitz, Shaobo Hou, Brendan O'Donoghue, Iurii Kemaev, Satinder Singh |
| 2021 | ICML | Reinforcement Learning of Implicit and Explicit Control Flow Instructions. | Ethan Brooks, Janarthanan Rajendran, Richard L. Lewis, Satinder Singh |
| 2021 | IJCAI | Reinforcement Learning for Sparse-Reward Object-Interaction Tasks in a First-person Simulated 3D Environment. | Wilka Carvalho, Anthony Liang, Kimin Lee, Sungryull Sohn, Honglak Lee, Richard L. Lewis, Satinder Singh |
| 2020 | AAAI | Modeling Probabilistic Commitments for Maintenance Is Inherently Harder than for Achievement. | Qi Zhang, Edmund H. Durfee, Satinder Singh |
| 2020 | AAAI | How Should an Agent Practice? | Janarthanan Rajendran, Richard L. Lewis, Vivek Veeriah, Honglak Lee, Satinder Singh |
| 2020 | AAAI | Querying to Find a Safe Policy under Uncertain Safety Constraints in Markov Decision Processes. | Shun Zhang, Edmund H. Durfee, Satinder Singh |
| 2020 | AISTATS | Sample Complexity of Reinforcement Learning using Linearly Combined Model Ensembles. | Aditya Modi, Nan Jiang, Ambuj Tewari, Satinder Singh |
| 2020 | ICLR | Behaviour Suite for Reinforcement Learning. | Ian Osband, Yotam Doron, Matteo Hessel, John Aslanides, Eren Sezener, Andre Saraiva, Katrina McKinney, Tor Lattimore, Csaba Szepesvri, Satinder Singh, Benjamin Van Roy, Richard S. Sutton, David Silver, Hado van Hasselt |
| 2020 | ICML | What Can Learned Intrinsic Rewards Capture? | Zeyu Zheng, Junhyuk Oh, Matteo Hessel, Zhongwen Xu, Manuel Kroiss, Hado van Hasselt, David Silver, Satinder Singh |
| 2019 | AAAI | Learning to Communicate and Solve Visual Blocks-World Tasks. | Qi Zhang, Richard L. Lewis, Satinder Singh, Edmund H. Durfee |
| 2019 | ICDM | Deep Reinforcement Learning for Multi-driver Vehicle Dispatching and Repositioning Problem. | John Holler, Risto Vuorio, Zhiwei (Tony) Qin, Xiaocheng Tang, Yan Jiao, Tiancheng Jin, Satinder Singh, Chenxi Wang, Jieping Ye |
| 2019 | IJCAI | Computational Strategies for the Trustworthy Pursuit and the Safe Modeling of Probabilistic Maintenance Commitments. | Qi Zhang, Edmund H. Durfee, Satinder Singh |
| 2019 | RANLP | NE-Table: A Neural key-value table for Named Entities. | Janarthanan Rajendran, Jatin Ganhotra, Xiaoxiao Guo, Mo Yu, Satinder Singh, Lazaros Polymenakos |
| 2018 | ALT | Markov Decision Processes with Continuous Side Information. | Aditya Modi, Nan Jiang, Satinder Singh, Ambuj Tewari |
| 2018 | EMNLP | Learning End-to-End Goal-Oriented Dialog with Multiple Answers. | Janarthanan Rajendran, Jatin Ganhotra, Satinder Singh, Lazaros Polymenakos |
| 2018 | ICML | Self-Imitation Learning. | Junhyuk Oh, Yijie Guo, Satinder Singh, Honglak Lee |
| 2018 | IJCAI | Minimax-Regret Querying on Side Effects for Safe Optimality in Factored Markov Decision Processes. | Shun Zhang, Edmund H. Durfee, Satinder Singh |
| 2017 | AAAI | A Stackelberg Game Model for Botnet Traffic Exfiltration. | Thanh Hong Nguyen, Michael P. Wellman, Satinder Singh |
| 2017 | ACL | Understanding and Predicting Empathic Behavior in Counseling Therapy. | Vernica Prez-Rosas, Rada Mihalcea, Kenneth Resnicow, Satinder Singh, Lawrence C. An |
| 2017 | CCS | Multi-Stage Attack Graph Security Games: Heuristic Strategies, with Empirical Game-Theoretic Analysis. | Thanh Hong Nguyen, Mason Wright, Michael P. Wellman, Satinder Singh |
| 2017 | EACL | Predicting Counselor Behaviors in Motivational Interviewing Encounters. | Vernica Prez-Rosas, Rada Mihalcea, Kenneth Resnicow, Satinder Singh, Lawrence C. An, Kathy J. Goggin, Delwyn Catley |
| 2017 | ICLR | Learning to Query, Reason, and Answer Questions On Ambiguous Texts. | Xiaoxiao Guo, Tim Klinger, Clemens Rosenbaum, Joseph P. Bigus, Murray Campbell, Ban Kawas, Kartik Talamadupula, Gerry Tesauro, Satinder Singh |
| 2017 | ICML | Zero-Shot Task Generalization with Multi-Task Deep Reinforcement Learning. | Junhyuk Oh, Satinder Singh, Honglak Lee, Pushmeet Kohli |
| 2016 | AAAI | Improving Predictive State Representations via Gradient Descent. | Nan Jiang, Alex Kulesza, Satinder Singh |
| 2016 | ICML | Control of Memory, Active Perception, and Action in Minecraft. | Junhyuk Oh, Valliappa Chockalingam, Satinder Singh, Honglak Lee |
| 2016 | IJCAI | Deep Learning for Reward Design to Improve Monte Carlo Tree Search in ATARI Games. | Xiaoxiao Guo, Satinder Singh, Richard L. Lewis, Honglak Lee |
| 2016 | IJCAI | The Dependence of Effective Planning Horizon on Model Accuracy. | Nan Jiang, Alex Kulesza, Satinder Singh, Richard L. Lewis |
| 2016 | IJCAI | On Structural Properties of MDPs that Bound Loss Due to Shallow Planning. | Nan Jiang, Satinder Singh, Ambuj Tewari |
| 2016 | IJCAI | Commitment Semantics for Sequential Decision Making under Reward Uncertainty. | Qi Zhang, Edmund H. Durfee, Satinder Singh, Anna Chen, Stefan J. Witwicki |
| 2016 | NAACL | Building a Motivational Interviewing Dataset. | Vernica Prez-Rosas, Rada Mihalcea, Kenneth Resnicow, Satinder Singh, Lawrence C. An |
| 2016 | UAI | Gradient Methods for Stackelberg Games. | Kareem Amin, Michael P. Wellman, Satinder Singh |
| 2015 | AAAI | Spectral Learning of Predictive State Representations with Insufficient Statistics. | Alex Kulesza, Nan Jiang, Satinder Singh |
| 2015 | AISTATS | Low-Rank Spectral Learning with Weighted Loss Functions. | Alex Kulesza, Nan Jiang, Satinder Singh |
| 2015 | ICML | Abstraction Selection in Model-based Reinforcement Learning. | Nan Jiang, Alex Kulesza, Satinder Singh |
| 2014 | AAAI | Predicting Postoperative Atrial Fibrillation from Independent ECG Components. | Chih-Chun Chia, James Blum, Zahi N. Karam, Satinder Singh, Zeeshan Syed |
| 2014 | AAAI | Evaluating Trauma Patients: Addressing Missing Covariates with Joint Optimization. | Alexander Van Esbroeck, Satinder Singh, Ilan Rubinfeld, Zeeshan Syed |
| 2014 | AISTATS | Characterizing EVOI-Sufficient k-Response Query Sets in Decision Problems. | Robert Cohn, Satinder Singh, Edmund H. Durfee |
| 2014 | AISTATS | Low-Rank Spectral Learning. | Alex Kulesza, N. Raj Rao, Satinder Singh |
| 2014 | ICASSP | Ecologically valid long-term mood monitoring of individuals with bipolar disorder using speech. | Zahi N. Karam, Emily Mower Provost, Satinder Singh, Jennifer Montgomery, Christopher Archer, Gloria Harrington, Melvin G. McInnis |
| 2013 | HCI | Linking Context to Evaluation in the Design of Safety Critical Interfaces. | Michael Feary, Dorrit Billman, Xiuli Chen, Andrew Howes, Richard L. Lewis, Lance Sherry, Satinder Singh |
| 2012 | AAAI | Security Games with Limited Surveillance. | Bo An, David Kempe, Christopher Kiekintveld, Eric Shieh, Satinder Singh, Milind Tambe, Yevgeniy Vorobeychik |
| 2012 | AAAI | Computing Stackelberg Equilibria in Discounted Stochastic Games. | Yevgeniy Vorobeychik, Satinder Singh |
| 2012 | AAMAS | Strong mitigation: nesting search for good policies within search for good reward. | Jeshua Bratman, Satinder Singh, Jonathan Sorg, Richard L. Lewis |
| 2012 | AAMAS | Learning and predicting dynamic networked behavior with graphical multiagent models. | Quang Duong, Michael P. Wellman, Satinder Singh, Michael J. Kearns |
| 2012 | AAMAS | Planning and evaluating multiagent influences under reward uncertainty. | Stefan J. Witwicki, Inn-Tung Chen, Edmund H. Durfee, Satinder Singh |
| 2011 | AAAI | Comparing Action-Query Strategies in Semi-Autonomous Agents. | Robert Cohn, Edmund H. Durfee, Satinder Singh |
| 2011 | AAAI | Optimal Rewards versus Leaf-Evaluation Heuristics in Planning Agents. | Jonathan Sorg, Satinder Singh, Richard L. Lewis |
| 2010 | ICML | Internal Rewards Mitigate Agent Boundedness. | Jonathan Sorg, Satinder Singh, Richard L. Lewis |
| 2010 | UAI | Variance-Based Rewards for Approximate Bayesian Reinforcement Learning. | Jonathan Sorg, Satinder Singh, Richard L. Lewis |
| 2009 | IJCAI | Learning Graphical Game Models. | Quang Duong, Yevgeniy Vorobeychik, Satinder Singh, Michael P. Wellman |
| 2009 | IJCAI | Maintaining Predictions over Time without a Model. | Erik Talvitie, Satinder Singh |
| 2008 | ICML | Efficiently learning linear-linear exponential family predictive representations of state. | David Wingate, Satinder Singh |
| 2008 | ISAIM | Predictive Linear-Gaussian Models of Dynamical Systems with Vector-Valued Actions and Observations. | Matthew R. Rudary, Satinder Singh |
| 2008 | ISAIM | Building Incomplete but Accurate Models. | Erik Talvitie, Britton Wolfe, Satinder Singh |
| 2008 | UAI | Knowledge Combination in Graphical Multiagent Models. | Quang Duong, Michael P. Wellman, Satinder Singh |
| 2007 | AAAI | Enabling Domain-Awareness for a Generic Natural Language Interface. | Yunyao Li, Ishan Chaudhuri, Huahai Yang, Satinder Singh, H. V. Jagadish |
| 2007 | AAAI | Abstraction in Predictive State Representations. | Vishal Soni, Satinder Singh |
| 2007 | IJCAI | An Experts Algorithm for Transfer Learning. | Erik Talvitie, Satinder Singh |
| 2007 | IJCAI | Relational Knowledge with Predictive State Representations. | David Wingate, Vishal Soni, Britton Wolfe, Satinder Singh |
| 2007 | SIGMOD | DaNaLIX: a domain-adaptive natural language interface for querying XML. | Yunyao Li, Ishan Chaudhuri, Huahai Yang, Satinder Singh, H. V. Jagadish |
| 2006 | AAAI | Using Homomorphisms to Transfer Options across Continuous Reinforcement Learning Domains. | Vishal Soni, Satinder Singh |
| 2006 | AAAI | Mixtures of Predictive Linear Gaussian Models for Nonlinear, Stochastic Dynamical Systems. | David Wingate, Satinder Singh |
| 2006 | ICML | Predictive linear-Gaussian models of controlled stochastic dynamical systems. | Matthew R. Rudary, Satinder Singh |
| 2006 | ICML | Kernel Predictive Linear Gaussian models for nonlinear stochastic dynamical systems. | David Wingate, Satinder Singh |
| 2006 | ICML | Predictive state representations with options. | Britton Wolfe, Satinder Singh |
| 2006 | UAI | Optimal Coordinated Planning Amongst Self-Interested Agents with Private State. | Ruggiero Cavallo, David C. Parkes, Satinder Singh |
| 2005 | AAAI | Planning in Models that Combine Memory with Predictive Representations of State. | Michael R. James, Satinder Singh |
| 2005 | ICML | Learning predictive state representations in dynamical systems without reset. | Britton Wolfe, Michael R. James, Satinder Singh |
| 2005 | IJCAI | Combining Memory and Landmarks with Predictive State Representations. | Michael R. James, Britton Wolfe, Satinder Singh |
| 2005 | IJCAI | Learning Payoff Functions in Infinite Games. | Yevgeniy Vorobeychik, Michael P. Wellman, Satinder Singh |
| 2005 | UAI | Predictive Linear-Gaussian Models of Stochastic Dynamical Systems. | Matthew R. Rudary, Satinder Singh, David Wingate |
| 2004 | ICML | Learning and discovery of predictive state representations in dynamical systems with reset. | Michael R. James, Satinder Singh |
| 2004 | ICML | Adaptive cognitive orthotics: combining reinforcement learning and constraint-based temporal reasoning. | Matthew R. Rudary, Satinder Singh, Martha E. Pollack |
| 2004 | ICMLA | Planning with predictive state representations. | Michael R. James, Satinder Singh, Michael L. Littman |
| 2004 | UAI | Predictive State Representations: A New Theory for Modeling Dynamical Systems. | Satinder Singh, Michael R. James, Matthew R. Rudary |
| 2003 | ICML | Learning Predictive State Representations. | Satinder Singh, Michael L. Littman, Nicholas K. Jong, David Pardoe, Peter Stone |
| 2002 | AAAI | CobotDS: A Spoken Dialogue System for Chat. | Michael J. Kearns, Charles Lee Isbell Jr., Satinder Singh, Diane J. Litman, Jessica Howe |
| 2001 | UAI | Graphical Models for Game Theory. | Michael J. Kearns, Michael L. Littman, Satinder Singh |
| 2000 | AAAI | Cobot in LambdaMOO: A Social Statistics Agent. | Charles Lee Isbell Jr., Michael J. Kearns, David P. Kormann, Satinder Singh, Peter Stone |
| 2000 | AAAI | Empirical Evaluation of a Reinforcement Learning Spoken Dialogue System. | Satinder Singh, Michael J. Kearns, Diane J. Litman, Marilyn A. Walker |
| 2000 | COLING | Automatic Optimization of Dialogue Management. | Diane J. Litman, Michael S. Kearns, Satinder Singh, Marilyn A. Walker |
| 2000 | COLT | Bias-Variance Error Bounds for Temporal Difference Updates. | Michael J. Kearns, Satinder Singh |
| 2000 | ICML | A Boosting Approach to Topic Spotting on Subdialogues. | Kary L. Myers, Michael J. Kearns, Satinder Singh, Marilyn A. Walker |
| 2000 | ICML | Eligibility Traces for Off-Policy Policy Evaluation. | Doina Precup, Richard S. Sutton, Satinder Singh |
| 2000 | UAI | Fast Planning in Stochastic Games. | Michael J. Kearns, Yishay Mansour, Satinder Singh |
| 2000 | UAI | Nash Convergence of Gradient Dynamics in General-Sum Games. | Satinder Singh, Michael J. Kearns, Yishay Mansour |
| 2000 | RoboCup | Reinforcement Learning for 3 vs. 2 Keepaway | Peter Stone, Richard S. Sutton, Satinder Singh |
| 1999 | UAI | On the Complexity of Policy Iteration. | Yishay Mansour, Satinder Singh |
| 1999 | UAI | Approximate Planning for Factored POMDPs using Belief State Simplification. | David A. McAllester, Satinder Singh |
| 1998 | ICML | Near-Optimal Reinforcement Learning in Polynominal Time. | Michael J. Kearns, Satinder Singh |
| 1998 | ICML | Using Eligibility Traces to Find the Best Memoryless Policy in Partially Observable Markov Decision Processes. | John Loch, Satinder Singh |
| 1998 | ICML | Intra-Option Learning about Temporally Abstract Actions. | Richard S. Sutton, Doina Precup, Satinder Singh |
| 1993 | USENIX | The Autofs Automounter. | Brent Callaghan, Satinder Singh |