Chandak, Yash

26 publications

AISTATS 2024 A/B Testing Under Interference with Partial Network Information Shiv Shankar, Ritwik Sinha, Yash Chandak, Saayan Mitra, Madalina Fiterau

ICLR 2024 Adaptive Instrument Design for Indirect Experiments Yash Chandak, Shiv Shankar, Vasilis Syrgkanis, Emma Brunskill

JMLR 2024 Data-Efficient Policy Evaluation Through Behavior Policy Search Josiah P. Hanna, Yash Chandak, Philip S. Thomas, Martha White, Peter Stone, Scott Niekum

NeurIPSW 2024 Information Directed Tree Search: Reasoning and Planning with Language Agents Yash Chandak, HyunJi Nam, Allen Nie, Jonathan Lee, Emma Brunskill

NeurIPS 2024 OPERA: Automatic Offline Policy Evaluation with Re-Weighted Aggregates of Multiple Estimators Allen Nie, Yash Chandak, Christina J. Yuan, Anirudhan Badrinath, Yannis Flet-Berliac, Emma Brunskill

AISTATS 2023 Asymptotically Unbiased Off-Policy Policy Evaluation When Reusing Old Data in Nonstationary Environments Vincent Liu, Yash Chandak, Philip Thomas, Martha White

NeurIPS 2023 Behavior Alignment via Reward Function Optimization Dhawal Gupta, Yash Chandak, Scott Jordan, Philip S. Thomas, Bruno C. da Silva

ICMLW 2023 In-Context Decision-Making from Supervised Pretraining Jonathan Lee, Annie Xie, Aldo Pacchiano, Yash Chandak, Chelsea Finn, Ofir Nachum, Emma Brunskill

ICML 2023 Representations and Exploration for Deep Reinforcement Learning Using Singular Value Decomposition Yash Chandak, Shantanu Thakoor, Zhaohan Daniel Guo, Yunhao Tang, Remi Munos, Will Dabney, Diana L Borsa

NeurIPS 2023 Supervised Pretraining Can Learn In-Context Reinforcement Learning Jonathan Lee, Annie Xie, Aldo Pacchiano, Yash Chandak, Chelsea Finn, Ofir Nachum, Emma Brunskill

ICML 2023 Understanding Self-Predictive Learning for Reinforcement Learning Yunhao Tang, Zhaohan Daniel Guo, Pierre Harvey Richemond, Bernardo Avila Pires, Yash Chandak, Remi Munos, Mark Rowland, Mohammad Gheshlaghi Azar, Charline Le Lan, Clare Lyle, András György, Shantanu Thakoor, Will Dabney, Bilal Piot, Daniele Calandriello, Michal Valko

NeurIPS 2022 Factored DRO: Factored Distributionally Robust Policies for Contextual Bandits Tong Mu, Yash Chandak, Tatsunori B Hashimoto, Emma Brunskill

NeurIPS 2022 Off-Policy Evaluation for Action-Dependent Non-Stationary Environments Yash Chandak, Shiv Shankar, Nathaniel Bastian, Bruno da Silva, Emma Brunskill, Philip S. Thomas

AAAI 2022 On Optimizing Interventions in Shared Autonomy Weihao Tan, David Koleczek, Siddhant Pradhan, Nicholas Perello, Vivek Chettiar, Vishal Rohra, Aaslesha Rajaram, Soundararajan Srinivasan, H. M. Sajjad Hossain, Yash Chandak

NeurIPSW 2022 Optimization Using Parallel Gradient Evaluations on Multiple Parameters Yash Chandak, Shiv Shankar, Venkata Gandikota, Philip S. Thomas, Arya Mazumdar

ICML 2021 High Confidence Generalization for Reinforcement Learning James Kostas, Yash Chandak, Scott M Jordan, Georgios Theocharous, Philip Thomas

AAAI 2021 High-Confidence Off-Policy (or Counterfactual) Variance Estimation Yash Chandak, Shiv Shankar, Philip S. Thomas

NeurIPS 2021 SOPE: Spectrum of Off-Policy Estimators Christina Yuan, Yash Chandak, Stephen Giguere, Philip S. Thomas, Scott Niekum

NeurIPS 2021 Universal Off-Policy Evaluation Yash Chandak, Scott Niekum, Bruno da Silva, Erik Learned-Miller, Emma Brunskill, Philip S. Thomas

ICML 2020 Evaluating the Performance of Reinforcement Learning Algorithms Scott Jordan, Yash Chandak, Daniel Cohen, Mengxue Zhang, Philip Thomas

AAAI 2020 Lifelong Learning with a Changing Action Set Yash Chandak, Georgios Theocharous, Chris Nota, Philip S. Thomas

ICML 2020 Optimizing for the Future in Non-Stationary MDPs Yash Chandak, Georgios Theocharous, Shiv Shankar, Martha White, Sridhar Mahadevan, Philip Thomas

ICMLW 2020 Optimizing for the Future in Non-Stationary MDPs Yash Chandak, Georgios Theocharous, Shiv Shankar, Martha White, Sridhar Mahadevan, Philip S. Thomas

AAAI 2020 Reinforcement Learning When All Actions Are Not Always Available Yash Chandak, Georgios Theocharous, Blossom Metevier, Philip S. Thomas

NeurIPS 2020 Towards Safe Policy Improvement for Non-Stationary MDPs Yash Chandak, Scott Jordan, Georgios Theocharous, Martha White, Philip S. Thomas

ICML 2019 Learning Action Representations for Reinforcement Learning Yash Chandak, Georgios Theocharous, James Kostas, Scott Jordan, Philip Thomas