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Satinder Singh

48 papers · 2000–2025 · 11 conferences · across top CS/AI conferences

Achievements

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+16 more ↓ 🧭 Keyword Pioneer 🐣 Hot Topic Early Bird πŸŒ‰ Interdisciplinary Bridge πŸ—ΊοΈ Taxonomy Completionist (16) 🌍 Conference Polyglot (11)
πŸ—ΊοΈ Taxonomy Completionist (16) 🧭 Keyword Pioneer 🐣 Hot Topic Early Bird 🌟 Keyword Trendsetter Combo (6) πŸ† Grand Slam πŸ‘₯ Mega-Team (27) 🌱 Topic Pioneer πŸ”¬ Deep Specialist (13) πŸ† Keyword Champion (2) πŸš€ Conference Pioneer ❓ The Questioner (2) ⚑ Prolific Year (6) πŸ’Ž Century Club (48) πŸ“ˆ Trend Setter πŸ”₯ Unstoppable (13) πŸ—ƒοΈ Keyword Collector (187)

Conferences

NIPS (10) ICML (9) ICLR (7) IJCAI (7) AAAI (6) AISTATS (4) ACL (1) ALT (1) COLING (1) EACL (1) EMNLP (1)

Top co-authors

Honglak Lee (9) Nan Jiang (8) Junhyuk Oh (8) Richard Lewis (7) Tom Zahavy (6) Edmund Durfee (5) Alex Kulesza (5) Xiaoxiao Guo (4) Janarthanan Rajendran (4) Sebastian Flennerhag (4)

Research topics

Reinforcement Learning (2)

Keywords

reinforcement learning (10) multi-agent system (4) neural network (3) markov decision process (3) model-based reinforcement learning (3) intrinsic reward (3) reward function (3) spectral learning (3) reward function learning (2) model-free reinforcement learning (2) predictive state representation (2) query optimization (2) deep reinforcement learning (2) text classification (2) attention mechanism (2) recurrent neural network (2) singular value decomposition (2) supervised learning (2) active learning (2) low-rank approximation (2)

Papers

Mastering Board Games by External and Internal Planning with Language Models ICML 2025 Genie: Generative Interactive Environments ICML 2024 Human-Timescale Adaptation in an Open-Ended Task Space ICML 2023 Discovering Evolution Strategies via Meta-Black-Box Optimization ICLR 2023 ReLOAD: Reinforcement Learning with Optimistic Ascent-Descent for Last-Iterate Convergence in Constrained MDPs ICML 2023 Discovering Policies with DOMiNO: Diversity Optimization Maintaining Near Optimality ICLR 2023 Composing Task Knowledge With Modular Successor Feature Approximators ICLR 2023 In-context Reinforcement Learning with Algorithm Distillation ICLR 2023 Adaptive Pairwise Weights for Temporal Credit Assignment AAAI 2022 On the Expressivity of Markov Reward (Extended Abstract) IJCAI 2022 Bootstrapped Meta-Learning ICLR 2022 Discovering a set of policies for the worst case reward ICLR 2021 Efficient Querying for Cooperative Probabilistic Commitments AAAI 2021 Reinforcement Learning of Implicit and Explicit Control Flow Instructions ICML 2021 Reinforcement Learning for Sparse-Reward Object-Interaction Tasks in a First-person Simulated 3D Environment IJCAI 2021 How Should an Agent Practice? AAAI 2020 Querying to Find a Safe Policy under Uncertain Safety Constraints in Markov Decision Processes AAAI 2020 Behaviour Suite for Reinforcement Learning ICLR 2020 Modeling Probabilistic Commitments for Maintenance Is Inherently Harder than for Achievement AAAI 2020 What Can Learned Intrinsic Rewards Capture? ICML 2020 Sample Complexity of Reinforcement Learning using Linearly Combined Model Ensembles AISTATS 2020 Learning to Communicate and Solve Visual Blocks-World Tasks AAAI 2019 No-Press Diplomacy: Modeling Multi-Agent Gameplay NIPS 2019 Hindsight Credit Assignment NIPS 2019 Discovery of Useful Questions as Auxiliary Tasks NIPS 2019 Learning End-to-End Goal-Oriented Dialog with Multiple Answers EMNLP 2018 Completing State Representations using Spectral Learning NIPS 2018 On Learning Intrinsic Rewards for Policy Gradient Methods NIPS 2018 Markov Decision Processes with Continuous Side Information ALT 2018 Self-Imitation Learning ICML 2018 Minimax-Regret Querying on Side Effects for Safe Optimality in Factored Markov Decision Processes IJCAI 2018 Predicting Counselor Behaviors in Motivational Interviewing Encounters EACL 2017 Zero-Shot Task Generalization with Multi-Task Deep Reinforcement Learning ICML 2017 Understanding and Predicting Empathic Behavior in Counseling Therapy ACL 2017 Value Prediction Network NIPS 2017 Repeated Inverse Reinforcement Learning NIPS 2017 Deep Learning for Reward Design to Improve Monte Carlo Tree Search in ATARI Games IJCAI 2016 The Dependence of Effective Planning Horizon on Model Accuracy IJCAI 2016 Commitment Semantics for Sequential Decision Making under Reward Uncertainty IJCAI 2016 On Structural Properties of MDPs that Bound Loss Due to Shallow Planning IJCAI 2016 Low-Rank Spectral Learning with Weighted Loss Functions AISTATS 2015 Abstraction Selection in Model-based Reinforcement Learning ICML 2015 Action-Conditional Video Prediction using Deep Networks in Atari Games NIPS 2015 Deep Learning for Real-Time Atari Game Play Using Offline Monte-Carlo Tree Search Planning NIPS 2014 Low-Rank Spectral Learning AISTATS 2014 Characterizing EVOI-Sufficient k-Response Query Sets in Decision Problems AISTATS 2014 Reward Mapping for Transfer in Long-Lived Agents NIPS 2013 Automatic Optimization of Dialogue Management COLING 2000