Satinder Singh
48 papers · 2000–2025 · 11 venues · across top CS/AI venues
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Achievements
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πΊοΈ Taxonomy Completionist (68) π Conference Polyglot Β· Gold π Academic Marathon Β· Ultra π Interdisciplinary Bridge Β· Silver π£ Hot Topic Early Bird
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Keyword Trendsetter Combo
(8)
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Grand Slam
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Mega-Team Β· Squad
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Deep Specialist
(14)
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Topic Evolution
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Keyword Champion
(2)
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Keyword Pioneer
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Trend Setter
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Keyword Collector
(222)
β
The Questioner
(2)
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Unstoppable Β· Silver
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Conference Pioneer
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Renaissance Researcher
(7)
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Century Club Β· Bronze
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Prolific Year Β· Productive
Venues
Top co-authors
Research topics
Machine Learning
(31)
Artificial Intelligence
(30)
Reinforcement Learning
(30)
Core AI
(27)
Methods
(25)
Learning Types Β· Machine Learning
(20)
Applications
(10)
Learning Paradigms Β· Artificial Intelligence
(10)
Optimization & Theory
(9)
Deep Learning
(8)
Learning Paradigms Β· Machine Learning
(6)
Core Methods
(5)
Mathematics & Optimization
(4)
Architectures
(4)
Learning Types Β· Deep Learning
(4)
Keywords
reinforcement learning
(16)
neural network
(4)
multi-agent system
(4)
intrinsic reward
(4)
spectral learning
(3)
reward function
(3)
model-based reinforcement learning
(3)
markov decision process
(3)
in-context learning
(3)
recurrent neural network
(2)
active learning
(2)
query optimization
(2)
autonomous agent
(2)
transfer learning
(2)
singular value decomposition
(2)
value function
(2)
supervised learning
(2)
text classification
(2)
low-rank approximation
(2)
attention mechanism
(2)
Papers
Mastering Board Games by External and Internal Planning with Language Models
ICML 2025
Genie: Generative Interactive Environments
ICML 2024
Composing Task Knowledge With Modular Successor Feature Approximators
ICLR 2023
Discovering Evolution Strategies via Meta-Black-Box Optimization
ICLR 2023
Discovering Policies with DOMiNO: Diversity Optimization Maintaining Near Optimality
ICLR 2023
Human-Timescale Adaptation in an Open-Ended Task Space
ICML 2023
In-context Reinforcement Learning with Algorithm Distillation
ICLR 2023
ReLOAD: Reinforcement Learning with Optimistic Ascent-Descent for Last-Iterate Convergence in Constrained MDPs
ICML 2023
Adaptive Pairwise Weights for Temporal Credit Assignment
AAAI 2022
Bootstrapped Meta-Learning
ICLR 2022
On the Expressivity of Markov Reward (Extended Abstract)
IJCAI 2022
Discovering a set of policies for the worst case reward
ICLR 2021
Efficient Querying for Cooperative Probabilistic Commitments
AAAI 2021
Reinforcement Learning for Sparse-Reward Object-Interaction Tasks in a First-person Simulated 3D Environment
IJCAI 2021
Reinforcement Learning of Implicit and Explicit Control Flow Instructions
ICML 2021
Behaviour Suite for Reinforcement Learning
ICLR 2020
How Should an Agent Practice?
AAAI 2020
Modeling Probabilistic Commitments for Maintenance Is Inherently Harder than for Achievement
AAAI 2020
Querying to Find a Safe Policy under Uncertain Safety Constraints in Markov Decision Processes
AAAI 2020
Sample Complexity of Reinforcement Learning using Linearly Combined Model Ensembles
AISTATS 2020
What Can Learned Intrinsic Rewards Capture?
ICML 2020
Discovery of Useful Questions as Auxiliary Tasks
NeurIPS 2019
Hindsight Credit Assignment
NeurIPS 2019
Learning to Communicate and Solve Visual Blocks-World Tasks
AAAI 2019
No-Press Diplomacy: Modeling Multi-Agent Gameplay
NeurIPS 2019
Completing State Representations using Spectral Learning
NeurIPS 2018
Learning End-to-End Goal-Oriented Dialog with Multiple Answers
EMNLP 2018
Markov Decision Processes with Continuous Side Information
ALT 2018
Minimax-Regret Querying on Side Effects for Safe Optimality in Factored Markov Decision Processes
IJCAI 2018
On Learning Intrinsic Rewards for Policy Gradient Methods
NeurIPS 2018
Self-Imitation Learning
ICML 2018
Predicting Counselor Behaviors in Motivational Interviewing Encounters
EACL 2017
Repeated Inverse Reinforcement Learning
NeurIPS 2017
Understanding and Predicting Empathic Behavior in Counseling Therapy
ACL 2017
Value Prediction Network
NeurIPS 2017
Zero-Shot Task Generalization with Multi-Task Deep Reinforcement Learning
ICML 2017
Commitment Semantics for Sequential Decision Making under Reward Uncertainty
IJCAI 2016
Deep Learning for Reward Design to Improve Monte Carlo Tree Search in ATARI Games
IJCAI 2016
On Structural Properties of MDPs that Bound Loss Due to Shallow Planning
IJCAI 2016
The Dependence of Effective Planning Horizon on Model Accuracy
IJCAI 2016
Abstraction Selection in Model-based Reinforcement Learning
ICML 2015
Action-Conditional Video Prediction using Deep Networks in Atari Games
NeurIPS 2015
Low-Rank Spectral Learning with Weighted Loss Functions
AISTATS 2015
Characterizing EVOI-Sufficient k-Response Query Sets in Decision Problems
AISTATS 2014
Deep Learning for Real-Time Atari Game Play Using Offline Monte-Carlo Tree Search Planning
NeurIPS 2014
Low-Rank Spectral Learning
AISTATS 2014
Reward Mapping for Transfer in Long-Lived Agents
NeurIPS 2013
Automatic Optimization of Dialogue Management
COLING 2000