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Yash Chandak — most-cited papers & profile · Reinforcement Learning
← authors
·
overview
Yash Chandak
19
papers ·
80
citations ·
8
h-index
University of Colorado System
Google Scholar ↗
Semantic Scholar ↗
OpenAlex ↗
Most-cited papers
Learning Action Representations for Reinforcement Learning
2019 · 22 citations
Evaluating the Performance of Reinforcement Learning Algorithms
2020 · 19 citations
Optimizing for the Future in Non-Stationary MDPs
2020 · 12 citations
Towards Safe Policy Improvement for Non-Stationary MDPs
2020 · 9 citations
Universal Off-Policy Evaluation
2021 · 3 citations
Off-Policy Evaluation for Action-Dependent Non-Stationary Environments
2023 · 3 citations
Reinforcement Learning for Strategic Recommendations
2020 · 2 citations
Behavior Alignment via Reward Function Optimization
2023 · 2 citations
Understanding Self-Predictive Learning for Reinforcement Learning
2022 · 1 citations
Representations and Exploration for Deep Reinforcement Learning using Singular Value Decomposition
2023 · 1 citations
Supervised Pretraining Can Learn In-Context Reinforcement Learning
2023 · 1 citations
Contrastive Policy Gradient: Aligning LLMs on sequence-level scores in a supervised-friendly fashion
2024
Classical Policy Gradient: Preserving Bellman's Principle of Optimality
2019
SOPE: Spectrum of Off-Policy Estimators
2021
Asymptotically Unbiased Off-Policy Policy Evaluation when Reusing Old Data in Nonstationary Environments
2023
Top co-authors
Philip S. Thomas
· 11
Georgios Theocharous
· 5
Bruno Castro da Silva
· 4
Martha White
· 3
Scott M. Jordan
· 3
Christina J. Yuan
· 2
Dhawal Gupta
· 2
Emma Brunskil
· 2
Emma Brunskill
· 2
James Kostas
· 2
Mohammad Gheshlaghi Azar
· 2
Scott M. Jordan
· 2
Topics
Offline RL
Policy Gradient
Exploration
Value-Based
Meta-RL
Safe RL
Model-Based RL
RLHF & Alignment
Multi-Agent