Yinlam Chow

According to our database, Yinlam Chow authored at least 55 papers between 2011 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2024

DynaMITE-RL: A Dynamic Model for Improved Temporal Meta-Reinforcement Learning.

Anthony Liang, Guy Tennenholtz, Chih-Wei Hsu, Yinlam Chow, Erdem Biyik, Craig Boutilier

CoRR, 2024

2023

Preference Elicitation with Soft Attributes in Interactive Recommendation.

Erdem Biyik, Fan Yao, Yinlam Chow, Alex Haig, Chih-Wei Hsu, Mohammad Ghavamzadeh, Craig Boutilier

CoRR, 2023

Factual and Personalized Recommendations using Language Models and Reinforcement Learning.

Jihwan Jeong, Yinlam Chow, Guy Tennenholtz, Chih-Wei Hsu, Azamat Tulepbergenov, Mohammad Ghavamzadeh, Craig Boutilier

CoRR, 2023

Demystifying Embedding Spaces using Large Language Models.

Guy Tennenholtz, Yinlam Chow, Chih-Wei Hsu, Jihwan Jeong, Lior Shani, Azamat Tulepbergenov, Deepak Ramachandran, Martin Mladenov, Craig Boutilier

CoRR, 2023

Offline Reinforcement Learning for Mixture-of-Expert Dialogue Management.

Dhawal Gupta, Yinlam Chow, Mohammad Ghavamzadeh, Craig Boutilier

CoRR, 2023

Offline Reinforcement Learning for Mixture-of-Expert Dialogue Management.

Dhawal Gupta, Yinlam Chow, Azamat Tulepbergenov, Mohammad Ghavamzadeh, Craig Boutilier

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

A Mixture-of-Expert Approach to RL-based Dialogue Management.

Yinlam Chow, Aza Tulepbergenov, Ofir Nachum, Dhawal Gupta, Moonkyung Ryu, Mohammad Ghavamzadeh, Craig Boutilier

Proceedings of the Eleventh International Conference on Learning Representations, 2023

2022

Dynamic Planning in Open-Ended Dialogue using Reinforcement Learning.

Deborah Cohen, Moonkyung Ryu, Yinlam Chow, Orgad Keller, Ido Greenberg, Avinatan Hassidim, Michael Fink, Yossi Matias, Idan Szpektor, Craig Boutilier, Gal Elidan

CoRR, 2022

A Mixture-of-Expert Approach to RL-based Dialogue Management.

Yinlam Chow, Aza Tulepbergenov, Ofir Nachum, Moonkyung Ryu, Mohammad Ghavamzadeh, Craig Boutilier

CoRR, 2022

SAFER: Data-Efficient and Safe Reinforcement Learning via Skill Acquisition.

Dylan Slack, Yinlam Chow, Bo Dai, Nevan Wichers

CoRR, 2022

Discovering Personalized Semantics for Soft Attributes in Recommender Systems using Concept Activation Vectors.

Christina Göpfert, Yinlam Chow, Chih-Wei Hsu, Ivan Vendrov, Tyler Lu, Deepak Ramachandran, Craig Boutilier

Proceedings of the WWW '22: The ACM Web Conference 2022, Virtual Event, Lyon, France, April 25, 2022

Efficient Risk-Averse Reinforcement Learning.

Ido Greenberg, Yinlam Chow, Mohammad Ghavamzadeh, Shie Mannor

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

2021

Safe Reinforcement Learning with Natural Language Constraints.

Tsung-Yen Yang, Michael Y. Hu, Yinlam Chow, Peter J. Ramadge, Karthik Narasimhan

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Variational Model-based Policy Optimization.

Yinlam Chow, Brandon Cui, Moonkyung Ryu, Mohammad Ghavamzadeh

Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence, 2021

Control-Aware Representations for Model-based Reinforcement Learning.

Brandon Cui, Yinlam Chow, Mohammad Ghavamzadeh

Proceedings of the 9th International Conference on Learning Representations, 2021

Non-Stationary Off-Policy Optimization.

Joey Hong, Branislav Kveton, Manzil Zaheer, Yinlam Chow, Amr Ahmed

Proceedings of the 24th International Conference on Artificial Intelligence and Statistics, 2021

2020

Non-Stationary Latent Bandits.

Joey Hong, Branislav Kveton, Manzil Zaheer, Yinlam Chow, Amr Ahmed, Mohammad Ghavamzadeh, Craig Boutilier

CoRR, 2020

Piecewise-Stationary Off-Policy Optimization.

Joey Hong, Branislav Kveton, Manzil Zaheer, Yinlam Chow, Amr Ahmed

CoRR, 2020

Latent Bandits Revisited.

Joey Hong, Branislav Kveton, Manzil Zaheer, Yinlam Chow, Amr Ahmed, Craig Boutilier

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

CoinDICE: Off-Policy Confidence Interval Estimation.

Bo Dai, Ofir Nachum, Yinlam Chow, Lihong Li, Csaba Szepesvári, Dale Schuurmans

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

BRPO: Batch Residual Policy Optimization.

Sungryull Sohn, Yinlam Chow, Jayden Ooi, Ofir Nachum, Honglak Lee, Ed H. Chi, Craig Boutilier

Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence, 2020

Predictive Coding for Locally-Linear Control.

Rui Shu, Tung Nguyen, Yinlam Chow, Tuan Pham, Khoat Than, Mohammad Ghavamzadeh, Stefano Ermon, Hung H. Bui

Proceedings of the 37th International Conference on Machine Learning, 2020

CAQL: Continuous Action Q-Learning.

Moonkyung Ryu, Yinlam Chow, Ross Anderson, Christian Tjandraatmadja, Craig Boutilier

Proceedings of the 8th International Conference on Learning Representations, 2020

Prediction, Consistency, Curvature: Representation Learning for Locally-Linear Control.

Nir Levine, Yinlam Chow, Rui Shu, Ang Li, Mohammad Ghavamzadeh, Hung Bui

Proceedings of the 8th International Conference on Learning Representations, 2020

Safe Policy Learning for Continuous Control.

Yinlam Chow, Ofir Nachum, Aleksandra Faust, Edgar A. Duéñez-Guzmán, Mohammad Ghavamzadeh

Proceedings of the 4th Conference on Robot Learning, 2020

2019

A Framework for Time-Consistent, Risk-Sensitive Model Predictive Control: Theory and Algorithms.

Sumeet Singh, Yinlam Chow, Anirudha Majumdar, Marco Pavone

IEEE Trans. Autom. Control., 2019

AlgaeDICE: Policy Gradient from Arbitrary Experience.

Ofir Nachum, Bo Dai, Ilya Kostrikov, Yinlam Chow, Lihong Li, Dale Schuurmans

CoRR, 2019

Lyapunov-based Safe Policy Optimization for Continuous Control.

Yinlam Chow, Ofir Nachum, Aleksandra Faust, Mohammad Ghavamzadeh, Edgar A. Duéñez-Guzmán

CoRR, 2019

DualDICE: Behavior-Agnostic Estimation of Discounted Stationary Distribution Corrections.

Ofir Nachum, Yinlam Chow, Bo Dai, Lihong Li

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Risk-Sensitive Generative Adversarial Imitation Learning.

Jonathan Lacotte, Mohammad Ghavamzadeh, Yinlam Chow, Marco Pavone

Proceedings of the 22nd International Conference on Artificial Intelligence and Statistics, 2019

2018

A Block Coordinate Ascent Algorithm for Mean-Variance Optimization.

Tengyang Xie, Bo Liu, Yangyang Xu, Mohammad Ghavamzadeh, Yinlam Chow, Daoming Lyu, Daesub Yoon

Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

A Lyapunov-based Approach to Safe Reinforcement Learning.

Yinlam Chow, Ofir Nachum, Edgar A. Duéñez-Guzmán, Mohammad Ghavamzadeh

Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

More Robust Doubly Robust Off-policy Evaluation.

Mehrdad Farajtabar, Yinlam Chow, Mohammad Ghavamzadeh

Proceedings of the 35th International Conference on Machine Learning, 2018

Path Consistency Learning in Tsallis Entropy Regularized MDPs.

Yinlam Chow, Ofir Nachum, Mohammad Ghavamzadeh

Proceedings of the 35th International Conference on Machine Learning, 2018

Imitation Learning from Visual Data with Multiple Intentions.

Aviv Tamar, Khashayar Rohanimanesh, Yinlam Chow, Chris Vigorito, Ben Goodrich, Michael Kahane, Derik Pridmore

Proceedings of the 6th International Conference on Learning Representations, 2018

2017

Sequential Decision Making With Coherent Risk.

Aviv Tamar, Yinlam Chow, Mohammad Ghavamzadeh, Shie Mannor

IEEE Trans. Autom. Control., 2017

Weighted SGD for $\ell_p$ Regression with Randomized Preconditioning.

Jiyan Yang, Yin-Lam Chow, Christopher Ré, Michael W. Mahoney

J. Mach. Learn. Res., 2017

Risk-Constrained Reinforcement Learning with Percentile Risk Criteria.

Yinlam Chow, Mohammad Ghavamzadeh, Lucas Janson, Marco Pavone

J. Mach. Learn. Res., 2017

A Framework for Time-Consistent, Risk-Averse Model Predictive Control: Theory and Algorithms.

Yin-Lam Chow, Sumeet Singh, Anirudha Majumdar, Marco Pavone

CoRR, 2017

Sequential Multiple Hypothesis Testing with Type I Error Control.

Alan Malek, Sumeet Katariya, Yinlam Chow, Mohammad Ghavamzadeh

Proceedings of the 20th International Conference on Artificial Intelligence and Statistics, 2017

2016

Distributed Online Modified Greedy Algorithm for Networked Storage Operation Under Uncertainty.

Junjie Qin, Yinlam Chow, Jiyan Yang, Ram Rajagopal

IEEE Trans. Smart Grid, 2016

Weighted SGD for <i>ℓ_p</i> Regression with Randomized Preconditioning.

Jiyan Yang, Yinlam Chow, Christopher Ré, Michael W. Mahoney

Proceedings of the Twenty-Seventh Annual ACM-SIAM Symposium on Discrete Algorithms, 2016

Safe Policy Improvement by Minimizing Robust Baseline Regret.

Mohammad Ghavamzadeh, Marek Petrik, Yinlam Chow

Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

Risk aversion in finite Markov Decision Processes using total cost criteria and average value at risk.

Stefano Carpin, Yinlam Chow, Marco Pavone

Proceedings of the 2016 IEEE International Conference on Robotics and Automation, 2016

2015

Trading Safety Versus Performance: Rapid Deployment of Robotic Swarms with Robust Performance Constraints.

Yinlam Chow, Marco Pavone, Brian M. Sadler, Stefano Carpin

CoRR, 2015

Policy Gradient for Coherent Risk Measures.

Aviv Tamar, Yinlam Chow, Mohammad Ghavamzadeh, Shie Mannor

Proceedings of the Advances in Neural Information Processing Systems 28: Annual Conference on Neural Information Processing Systems 2015, 2015

Risk-Sensitive and Robust Decision-Making: a CVaR Optimization Approach.

Yinlam Chow, Aviv Tamar, Shie Mannor, Marco Pavone

Proceedings of the Advances in Neural Information Processing Systems 28: Annual Conference on Neural Information Processing Systems 2015, 2015

Real-time Bidding based Vehicle Sharing.

Yinlam Chow, Jia Yuan Yu

Proceedings of the 2015 International Conference on Autonomous Agents and Multiagent Systems, 2015

2014

Algorithms for CVaR Optimization in MDPs.

Yinlam Chow, Mohammad Ghavamzadeh

Proceedings of the Advances in Neural Information Processing Systems 27: Annual Conference on Neural Information Processing Systems 2014, 2014

Modeling and online control of generalized energy storage networks.

Junjie Qin, Yinlam Chow, Jiyan Yang, Ram Rajagopal

Proceedings of the Fifth International Conference on Future Energy Systems, 2014

Weighted difference approximation of value functions for slow-discounting Markov Decision Processes.

Yinlam Chow, Junjie Qin

Proceedings of the 53rd IEEE Conference on Decision and Control, 2014

A framework for time-consistent, risk-averse model predictive control: Theory and algorithms.

Yin-Lam Chow, Marco Pavone

Proceedings of the American Control Conference, 2014

2013

A uniform-grid discretization algorithm for stochastic optimal control with risk constraints.

Yin-Lam Chow, Marco Pavone

Proceedings of the 52nd IEEE Conference on Decision and Control, 2013

Stochastic optimal control with dynamic, time-consistent risk constraints.

Yin-Lam Chow, Marco Pavone

Proceedings of the American Control Conference, 2013

2011

A decentralized control technique for vehicle chassis control.

Carlos Villegas, Yin-Lam Chow, Martin J. Corless, Robert Shorten, Wynita M. Griggs

Proceedings of the 50th IEEE Conference on Decision and Control and European Control Conference, 2011