Rahul Jain
21 papers · 2017–2026 · 7 venues · across top CS/AI venues
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Achievements
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Keyword Champion
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Renaissance Researcher
(5)
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Conference Pioneer
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Century Club Β· Bronze
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Top co-authors
Research topics
Machine Learning
(19)
Reinforcement Learning
(14)
Methods
(14)
Optimization & Theory
(13)
Learning Types
(8)
Artificial Intelligence
(7)
Core AI
(7)
Mathematics & Optimization
(4)
Optimization
(4)
Core Methods
(2)
Interdisciplinary
(1)
Natural Language Processing
(1)
Application Areas
(1)
Applications Β· Natural Language Processing
(1)
Applications Β· Reinforcement Learning
(1)
Keywords
regret bound
(7)
reinforcement learning
(6)
markov decision process
(4)
online learning
(4)
posterior sampling
(3)
imitation learning
(3)
policy optimization
(3)
stochastic shortest path
(3)
average-reward mdp
(3)
bayesian inference
(2)
bayesian regret
(2)
constraint violation
(2)
thompson sampling
(2)
no-regret learning
(2)
offline learning
(2)
constrained markov decision process
(2)
function approximation
(2)
partially observable markov decision process
(2)
regret minimization
(2)
kernel density estimation
(2)
Papers
Balance Equation-based Distributionally Robust Offline Imitation Learning
L4DC 2026
Efficient Decentralized Learning of Generalized Quantal Response Equilibrium
UAI 2026
A Safe Bayesian Learning Algorithm for Constrained MDPs with Bounded Constraint Violation
AISTATS 2025
Conditional Kernel Imitation Learning for Continuous State Environments
L4DC 2025
Markov Balance Satisfaction Improves Performance in Strictly Batch Offline Imitation Learning
AAAI 2025
ACPO: A Policy Optimization Algorithm for Average MDPs with Constraints
ICML 2024
e-COP : Episodic Constrained Optimization of Policies
NeurIPS 2024
Leveraging Demonstrations to Improve Online Learning: Quality Matters
ICML 2023
Posterior sampling-based online learning for the stochastic shortest path model
UAI 2023
Improved No-Regret Algorithms for Stochastic Shortest Path with Linear MDP
ICML 2022
Learning Infinite-horizon Average-reward Markov Decision Process with Constraints
ICML 2022
Matrix Multiplicative Weights Updates in Quantum Zero-Sum Games: Conservation Laws & Recurrence
NeurIPS 2022
Online Learning for Unknown Partially Observable MDPs
AISTATS 2022
Optimal control of partially observable Markov decision processes with finite linear temporal logic constraints
UAI 2022
A Case Study of Efficacy and Challenges in Practical Human-in-Loop Evaluation of NLP Systems Using Checklist
EACL 2021
A Sample-Efficient Algorithm for Episodic Finite-Horizon MDP with Constraints
AAAI 2021
Implicit Finite-Horizon Approximation and Efficient Optimal Algorithms for Stochastic Shortest Path
NeurIPS 2021
Learning Infinite-horizon Average-reward MDPs with Linear Function Approximation
AISTATS 2021
Model-free Reinforcement Learning in Infinite-horizon Average-reward Markov Decision Processes
ICML 2020
Approximate Relative Value Learning for Average-reward Continuous State MDPs
UAI 2019
Learning Unknown Markov Decision Processes: A Thompson Sampling Approach
NeurIPS 2017