Yinlam Chow

Publication Activity (10 Years)

Years Active: 2014-2024
Publications (10 Years): 61

Top Topics

Decision Process

Markov Decision Processes

Reinforcement Learning

Top Venues

Publications

Guy Tennenholtz, Yinlam Chow, Chih-Wei Hsu, Jihwan Jeong, Lior Shani, Azamat Tulepbergenov, Deepak Ramachandran, Martin Mladenov, Craig Boutilier
Demystifying Embedding Spaces using Large Language Models. ICLR (2024)
Anthony Liang, Guy Tennenholtz, Chih-Wei Hsu, Yinlam Chow, Erdem Biyik, Craig Boutilier
DynaMITE-RL: A Dynamic Model for Improved Temporal Meta-Reinforcement Learning. CoRR (2024)
Guy Tennenholtz, Yinlam Chow, Chih-Wei Hsu, Lior Shani, Ethan Liang, Craig Boutilier
Embedding-Aligned Language Models. CoRR (2024)
Guy Tennenholtz, Yinlam Chow, Chih-Wei Hsu, Jihwan Jeong, Lior Shani, Azamat Tulepbergenov, Deepak Ramachandran, Martin Mladenov, Craig Boutilier
Demystifying Embedding Spaces using Large Language Models. CoRR (2023)
Yinlam Chow, Aza Tulepbergenov, Ofir Nachum, Dhawal Gupta, Moonkyung Ryu, Mohammad Ghavamzadeh, Craig Boutilier
A Mixture-of-Expert Approach to RL-based Dialogue Management. ICLR (2023)
Dhawal Gupta, Yinlam Chow, Mohammad Ghavamzadeh, Craig Boutilier
Offline Reinforcement Learning for Mixture-of-Expert Dialogue Management. CoRR (2023)
Erdem Biyik, Fan Yao, Yinlam Chow, Alex Haig, Chih-Wei Hsu, Mohammad Ghavamzadeh, Craig Boutilier
Preference Elicitation with Soft Attributes in Interactive Recommendation. CoRR (2023)
Dhawal Gupta, Yinlam Chow, Azamat Tulepbergenov, Mohammad Ghavamzadeh, Craig Boutilier
Offline Reinforcement Learning for Mixture-of-Expert Dialogue Management. NeurIPS (2023)
Jihwan Jeong, Yinlam Chow, Guy Tennenholtz, Chih-Wei Hsu, Azamat Tulepbergenov, Mohammad Ghavamzadeh, Craig Boutilier
Factual and Personalized Recommendations using Language Models and Reinforcement Learning. CoRR (2023)
Dylan Slack, Yinlam Chow, Bo Dai, Nevan Wichers
SAFER: Data-Efficient and Safe Reinforcement Learning via Skill Acquisition. CoRR (2022)
Deborah Cohen, Moonkyung Ryu, Yinlam Chow, Orgad Keller, Ido Greenberg, Avinatan Hassidim, Michael Fink, Yossi Matias, Idan Szpektor, Craig Boutilier, Gal Elidan
Dynamic Planning in Open-Ended Dialogue using Reinforcement Learning. CoRR (2022)
Christina Göpfert, Yinlam Chow, Chih-Wei Hsu, Ivan Vendrov, Tyler Lu, Deepak Ramachandran, Craig Boutilier
Discovering Personalized Semantics for Soft Attributes in Recommender Systems using Concept Activation Vectors. WWW (2022)
Ido Greenberg, Yinlam Chow, Mohammad Ghavamzadeh, Shie Mannor
Efficient Risk-Averse Reinforcement Learning. NeurIPS (2022)
Yinlam Chow, Aza Tulepbergenov, Ofir Nachum, Moonkyung Ryu, Mohammad Ghavamzadeh, Craig Boutilier
A Mixture-of-Expert Approach to RL-based Dialogue Management. CoRR (2022)
Christina Göpfert, Yinlam Chow, Chih-Wei Hsu, Ivan Vendrov, Tyler Lu, Deepak Ramachandran, Craig Boutilier
Discovering Personalized Semantics for Soft Attributes in Recommender Systems using Concept Activation Vectors. CoRR (2022)
Ido Greenberg, Yinlam Chow, Mohammad Ghavamzadeh, Shie Mannor
Efficient Risk-Averse Reinforcement Learning. CoRR (2022)
Brandon Cui, Yinlam Chow, Mohammad Ghavamzadeh
Control-Aware Representations for Model-based Reinforcement Learning. ICLR (2021)
Tsung-Yen Yang, Michael Y. Hu, Yinlam Chow, Peter J. Ramadge, Karthik Narasimhan
Safe Reinforcement Learning with Natural Language Constraints. NeurIPS (2021)
Yinlam Chow, Brandon Cui, Moonkyung Ryu, Mohammad Ghavamzadeh
Variational Model-based Policy Optimization. IJCAI (2021)
Joey Hong, Branislav Kveton, Manzil Zaheer, Yinlam Chow, Amr Ahmed
Non-Stationary Off-Policy Optimization. AISTATS (2021)
Tsung-Yen Yang, Michael Hu, Yinlam Chow, Peter J. Ramadge, Karthik Narasimhan
Safe Reinforcement Learning with Natural Language Constraints. CoRR (2020)
Rui Shu, Tung Nguyen, Yinlam Chow, Tuan Pham, Khoat Than, Mohammad Ghavamzadeh, Stefano Ermon, Hung H. Bui
Predictive Coding for Locally-Linear Control. ICML (2020)
Rui Shu, Tung Nguyen, Yinlam Chow, Tuan Pham, Khoat Than, Mohammad Ghavamzadeh, Stefano Ermon, Hung H. Bui
Predictive Coding for Locally-Linear Control. CoRR (2020)
Joey Hong, Branislav Kveton, Manzil Zaheer, Yinlam Chow, Amr Ahmed
Piecewise-Stationary Off-Policy Optimization. CoRR (2020)
Joey Hong, Branislav Kveton, Manzil Zaheer, Yinlam Chow, Amr Ahmed, Mohammad Ghavamzadeh, Craig Boutilier
Non-Stationary Latent Bandits. CoRR (2020)
Joey Hong, Branislav Kveton, Manzil Zaheer, Yinlam Chow, Amr Ahmed, Craig Boutilier
Latent Bandits Revisited. CoRR (2020)
Bo Dai, Ofir Nachum, Yinlam Chow, Lihong Li, Csaba Szepesvári, Dale Schuurmans
CoinDICE: Off-Policy Confidence Interval Estimation. NeurIPS (2020)
Moonkyung Ryu, Yinlam Chow, Ross Anderson, Christian Tjandraatmadja, Craig Boutilier
CAQL: Continuous Action Q-Learning. ICLR (2020)
Joey Hong, Branislav Kveton, Manzil Zaheer, Yinlam Chow, Amr Ahmed, Craig Boutilier
Latent Bandits Revisited. NeurIPS (2020)
Sungryull Sohn, Yinlam Chow, Jayden Ooi, Ofir Nachum, Honglak Lee, Ed Chi, Craig Boutilier
BRPO: Batch Residual Policy Optimization. IJCAI (2020)
Brandon Cui, Yinlam Chow, Mohammad Ghavamzadeh
Control-Aware Representations for Model-based Reinforcement Learning. CoRR (2020)
Nir Levine, Yinlam Chow, Rui Shu, Ang Li, Mohammad Ghavamzadeh, Hung Bui
Prediction, Consistency, Curvature: Representation Learning for Locally-Linear Control. ICLR (2020)
Yinlam Chow, Brandon Cui, Moonkyung Ryu, Mohammad Ghavamzadeh
Variational Model-based Policy Optimization. CoRR (2020)
Yinlam Chow, Ofir Nachum, Aleksandra Faust, Edgar A. Duéñez-Guzmán, Mohammad Ghavamzadeh
Safe Policy Learning for Continuous Control. CoRL (2020)
Sungryull Sohn, Yinlam Chow, Jayden Ooi, Ofir Nachum, Honglak Lee, Ed Chi, Craig Boutilier
BRPO: Batch Residual Policy Optimization. CoRR (2020)
Bo Dai, Ofir Nachum, Yinlam Chow, Lihong Li, Csaba Szepesvári, Dale Schuurmans
CoinDICE: Off-Policy Confidence Interval Estimation. CoRR (2020)
Yinlam Chow, Ofir Nachum, Aleksandra Faust, Mohammad Ghavamzadeh, Edgar A. Duéñez-Guzmán
Lyapunov-based Safe Policy Optimization for Continuous Control. CoRR (2019)
Sumeet Singh, Yinlam Chow, Anirudha Majumdar, Marco Pavone
A Framework for Time-Consistent, Risk-Sensitive Model Predictive Control: Theory and Algorithms. IEEE Trans. Autom. Control. 64 (7) (2019)
Ofir Nachum, Bo Dai, Ilya Kostrikov, Yinlam Chow, Lihong Li, Dale Schuurmans
AlgaeDICE: Policy Gradient from Arbitrary Experience. CoRR (2019)
Ofir Nachum, Yinlam Chow, Bo Dai, Lihong Li
DualDICE: Behavior-Agnostic Estimation of Discounted Stationary Distribution Corrections. NeurIPS (2019)
Ofir Nachum, Yinlam Chow, Bo Dai, Lihong Li
DualDICE: Behavior-Agnostic Estimation of Discounted Stationary Distribution Corrections. CoRR (2019)
Moonkyung Ryu, Yinlam Chow, Ross Anderson, Christian Tjandraatmadja, Craig Boutilier
CAQL: Continuous Action Q-Learning. CoRR (2019)
Jonathan Lacotte, Mohammad Ghavamzadeh, Yinlam Chow, Marco Pavone
Risk-Sensitive Generative Adversarial Imitation Learning. AISTATS (2019)
Nir Levine, Yinlam Chow, Rui Shu, Ang Li, Mohammad Ghavamzadeh, Hung Bui
Prediction, Consistency, Curvature: Representation Learning for Locally-Linear Control. CoRR (2019)
Aviv Tamar, Khashayar Rohanimanesh, Yinlam Chow, Chris Vigorito, Ben Goodrich, Michael Kahane, Derik Pridmore
Imitation Learning from Visual Data with Multiple Intentions. ICLR (Poster) (2018)
Jonathan Lacotte, Yinlam Chow, Mohammad Ghavamzadeh, Marco Pavone
Risk-Sensitive Generative Adversarial Imitation Learning. CoRR (2018)
Yinlam Chow, Ofir Nachum, Edgar A. Duéñez-Guzmán, Mohammad Ghavamzadeh
A Lyapunov-based Approach to Safe Reinforcement Learning. CoRR (2018)
Bo Liu, Tengyang Xie, Yangyang Xu, Mohammad Ghavamzadeh, Yinlam Chow, Daoming Lyu, Daesub Yoon
A Block Coordinate Ascent Algorithm for Mean-Variance Optimization. CoRR (2018)
Yinlam Chow, Ofir Nachum, Edgar A. Duéñez-Guzmán, Mohammad Ghavamzadeh
A Lyapunov-based Approach to Safe Reinforcement Learning. NeurIPS (2018)
Mehrdad Farajtabar, Yinlam Chow, Mohammad Ghavamzadeh
More Robust Doubly Robust Off-policy Evaluation. ICML (2018)
Mehrdad Farajtabar, Yinlam Chow, Mohammad Ghavamzadeh
More Robust Doubly Robust Off-policy Evaluation. CoRR (2018)
Tengyang Xie, Bo Liu, Yangyang Xu, Mohammad Ghavamzadeh, Yinlam Chow, Daoming Lyu, Daesub Yoon
A Block Coordinate Ascent Algorithm for Mean-Variance Optimization. NeurIPS (2018)
Yinlam Chow, Ofir Nachum, Mohammad Ghavamzadeh
Path Consistency Learning in Tsallis Entropy Regularized MDPs. ICML (2018)
Ofir Nachum, Yinlam Chow, Mohammad Ghavamzadeh
Path Consistency Learning in Tsallis Entropy Regularized MDPs. CoRR (2018)
Aviv Tamar, Yinlam Chow, Mohammad Ghavamzadeh, Shie Mannor
Sequential Decision Making With Coherent Risk. IEEE Trans. Autom. Control. 62 (7) (2017)
Yinlam Chow, Mohammad Ghavamzadeh, Lucas Janson, Marco Pavone
Risk-Constrained Reinforcement Learning with Percentile Risk Criteria. J. Mach. Learn. Res. 18 (2017)
Alan Malek, Sumeet Katariya, Yinlam Chow, Mohammad Ghavamzadeh
Sequential Multiple Hypothesis Testing with Type I Error Control. AISTATS (2017)
Jiyan Yang, Yinlam Chow, Christopher Ré, Michael W. Mahoney
Regression with Randomized Preconditioning. SODA (2016)
Junjie Qin, Yinlam Chow, Jiyan Yang, Ram Rajagopal
Distributed Online Modified Greedy Algorithm for Networked Storage Operation Under Uncertainty. IEEE Trans. Smart Grid 7 (2) (2016)
Mohammad Ghavamzadeh, Marek Petrik, Yinlam Chow
Safe Policy Improvement by Minimizing Robust Baseline Regret. NIPS (2016)
Stefano Carpin, Yinlam Chow, Marco Pavone
Risk aversion in finite Markov Decision Processes using total cost criteria and average value at risk. ICRA (2016)
Yinlam Chow, Aviv Tamar, Shie Mannor, Marco Pavone
Risk-Sensitive and Robust Decision-Making: a CVaR Optimization Approach. NIPS (2015)
Yinlam Chow, Jia Yuan Yu
Real-time Bidding based Vehicle Sharing. CoRR (2015)
Aviv Tamar, Yinlam Chow, Mohammad Ghavamzadeh, Shie Mannor
Policy Gradient for Coherent Risk Measures. CoRR (2015)
Yinlam Chow, Marco Pavone, Brian M. Sadler, Stefano Carpin
Trading Safety Versus Performance: Rapid Deployment of Robotic Swarms with Robust Performance Constraints. CoRR (2015)
Aviv Tamar, Yinlam Chow, Mohammad Ghavamzadeh, Shie Mannor
Policy Gradient for Coherent Risk Measures. NIPS (2015)
Yinlam Chow, Mohammad Ghavamzadeh, Lucas Janson, Marco Pavone
Risk-Constrained Reinforcement Learning with Percentile Risk Criteria. CoRR (2015)
Yinlam Chow, Jia Yuan Yu
Real-time Bidding based Vehicle Sharing. AAMAS (2015)
Yinlam Chow, Aviv Tamar, Shie Mannor, Marco Pavone
Risk-Sensitive and Robust Decision-Making: a CVaR Optimization Approach. CoRR (2015)
Junjie Qin, Yinlam Chow, Jiyan Yang, Ram Rajagopal
Modeling and online control of generalized energy storage networks. e-Energy (2014)
Yinlam Chow, Junjie Qin
Weighted difference approximation of value functions for slow-discounting Markov Decision Processes. CDC (2014)
Yinlam Chow, Mohammad Ghavamzadeh
Algorithms for CVaR Optimization in MDPs. CoRR (2014)
Yinlam Chow, Mohammad Ghavamzadeh
Algorithms for CVaR Optimization in MDPs. NIPS (2014)