R. Srikant
17 papers · 2015–2025 · 7 conferences · across top CS/AI conferences
Achievements
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π Academic Marathon (10) π Interdisciplinary Bridge π§ Keyword Pioneer π Conference Polyglot (7) π Cross-Pollinator (10)
π
Cross-Pollinator
(10)
πΊοΈ
Taxonomy Completionist
(21)
π
Keyword Champion
π
Grand Slam
π
Conference Pioneer
ποΈ
Keyword Collector
(63)
π
Century Club
(17)
β‘
Prolific Year
(5)
Conferences
NIPS (6)
ICLR (3)
ICML (3)
AISTATS (2)
AAAI (1)
COLT (1)
L4DC (1)
Top co-authors
Keywords
reinforcement learning
(4)
stochastic approximation
(3)
policy iteration
(2)
binary classification
(1)
neural network optimization
(1)
loss landscape
(1)
function approximation
(1)
exploration-exploitation tradeoff
(1)
value function
(1)
mean squared error
(1)
learning to rank
(1)
mean-square error
(1)
asymptotic analysis
(1)
adaptive learning rate
(1)
game theory
(1)
collaborative learning
(1)
finite-time analysis
(1)
risk-sensitive mdps
(1)
linear convergence
(1)
temporal difference learning
(1)
Papers
Reinforcement Learning with Segment Feedback
ICML 2025
Decentralized and Uncoordinated Learning of Stable Matchings: A Game-Theoretic Approach
AAAI 2025
Global Convergence of Policy Gradient in Average Reward MDPs
ICLR 2025
Exploration-Driven Policy Optimization in RLHF: Theoretical Insights on Efficient Data Utilization
ICML 2024
Cascading Reinforcement Learning
ICLR 2024
Modified Policy Iteration for Exponential Cost Risk Sensitive MDPs
L4DC 2023
Performance Bounds for Policy-Based Average Reward Reinforcement Learning Algorithms
NIPS 2023
Learning While Scheduling in Multi-Server Systems With Unknown Statistics: MaxWeight with Discounted UCB
AISTATS 2023
On The Convergence Of Policy Iteration-Based Reinforcement Learning With Monte Carlo Policy Evaluation
AISTATS 2023
Collaborative Multi-Agent Heterogeneous Multi-Armed Bandits
ICML 2023
Minimax Regret for Cascading Bandits
NIPS 2022
The Mean-Squared Error of Double Q-Learning
NIPS 2020
Finite-Time Error Bounds For Linear Stochastic Approximation andTD Learning
COLT 2019
Finite-Time Performance Bounds and Adaptive Learning Rate Selection for Two Time-Scale Reinforcement Learning
NIPS 2019
Enhancing The Reliability of Out-of-distribution Image Detection in Neural Networks
ICLR 2018
Adding One Neuron Can Eliminate All Bad Local Minima
NIPS 2018
Algorithms with Logarithmic or Sublinear Regret for Constrained Contextual Bandits
NIPS 2015