Yinlam Chow - RankMe

82 papers A* 25A 4Misc 1Journal 45Unranked 7

Year	Rank	Type	Title / Venue / Authors
2025	J	`jnl`	Descriptive History Representations: Learning Representations by Answering Questions. CoRR Guy Tennenholtz, Jihwan Jeong, Chih-Wei Hsu, Yinlam Chow, Craig Boutilier
2025	A*	`conf`	Inference-Aware Fine-Tuning for Best-of-N Sampling in Large Language Models. ICLR Yinlam Chow, Guy Tennenholtz, Izzeddin Gur, Vincent Zhuang, Bo Dai, Aviral Kumar, Rishabh Agarwal, Sridhar Thiagarajan, Craig Boutilier, Aleksandra Faust
2025	A*	`conf`	Preference Adaptive and Sequential Text-to-Image Generation. ICML Ofir Nabati, Guy Tennenholtz, Chih-Wei Hsu, Moonkyung Ryu, Deepak Ramachandran, Yinlam Chow, Xiang Li, Craig Boutilier
2025	J	`jnl`	Synthetic Dialogue Generation for Interactive Conversational Elicitation & Recommendation (ICER). CoRR Moonkyung Ryu, Chih-Wei Hsu, Yinlam Chow, Mohammad Ghavamzadeh, Craig Boutilier
2024	A*	`conf`	Demystifying Embedding Spaces using Large Language Models. ICLR Guy Tennenholtz, Yinlam Chow, Chih-Wei Hsu, Jihwan Jeong, Lior Shani, Azamat Tulepbergenov, Deepak Ramachandran, Martin Mladenov, Craig Boutilier
2024	J	`jnl`	Discovering Personalized Semantics for Soft Attributes in Recommender Systems Using Concept Activation Vectors. Trans. Recomm. Syst. Christina Göpfert, Alex Haig, Chih-Wei Hsu, Yinlam Chow, Ivan Vendrov, Tyler Lu, Deepak Ramachandran, Hubert Pham, Mohammad Ghavamzadeh, Craig Boutilier
2024	A*	`conf`	DynaMITE-RL: A Dynamic Model for Improved Temporal Meta-Reinforcement Learning. NeurIPS Anthony Liang, Guy Tennenholtz, Chih-Wei Hsu, Yinlam Chow, Erdem Biyik, Craig Boutilier
2024	J	`jnl`	DynaMITE-RL: A Dynamic Model for Improved Temporal Meta-Reinforcement Learning. CoRR Anthony Liang, Guy Tennenholtz, Chih-Wei Hsu, Yinlam Chow, Erdem Biyik, Craig Boutilier
2024	A*	`conf`	Embedding-Aligned Language Models. NeurIPS Guy Tennenholtz, Yinlam Chow, Chih-Wei Hsu, Lior Shani, Yi Liang, Craig Boutilier
2024	J	`jnl`	Embedding-Aligned Language Models. CoRR Guy Tennenholtz, Yinlam Chow, Chih-Wei Hsu, Lior Shani, Ethan Liang, Craig Boutilier
2024	J	`jnl`	Inference-Aware Fine-Tuning for Best-of-N Sampling in Large Language Models. CoRR Yinlam Chow, Guy Tennenholtz, Izzeddin Gur, Vincent Zhuang, Bo Dai, Sridhar Thiagarajan, Craig Boutilier, Rishabh Agarwal, Aviral Kumar, Aleksandra Faust
2024	J	`jnl`	Personalized and Sequential Text-to-Image Generation. CoRR Ofir Nabati, Guy Tennenholtz, Chih-Wei Hsu, Moonkyung Ryu, Deepak Ramachandran, Yinlam Chow, Xiang Li, Craig Boutilier
2023	A*	`conf`	A Mixture-of-Expert Approach to RL-based Dialogue Management. ICLR Yinlam Chow, Aza Tulepbergenov, Ofir Nachum, Dhawal Gupta, Moonkyung Ryu, Mohammad Ghavamzadeh, Craig Boutilier
2023	J	`jnl`	Demystifying Embedding Spaces using Large Language Models. CoRR Guy Tennenholtz, Yinlam Chow, Chih-Wei Hsu, Jihwan Jeong, Lior Shani, Azamat Tulepbergenov, Deepak Ramachandran, Martin Mladenov, Craig Boutilier
2023	J	`jnl`	Factual and Personalized Recommendations using Language Models and Reinforcement Learning. CoRR Jihwan Jeong, Yinlam Chow, Guy Tennenholtz, Chih-Wei Hsu, Azamat Tulepbergenov, Mohammad Ghavamzadeh, Craig Boutilier
2023	A*	`conf`	Offline Reinforcement Learning for Mixture-of-Expert Dialogue Management. NeurIPS Dhawal Gupta, Yinlam Chow, Azamat Tulepbergenov, Mohammad Ghavamzadeh, Craig Boutilier
2023	J	`jnl`	Offline Reinforcement Learning for Mixture-of-Expert Dialogue Management. CoRR Dhawal Gupta, Yinlam Chow, Mohammad Ghavamzadeh, Craig Boutilier
2023	J	`jnl`	Preference Elicitation with Soft Attributes in Interactive Recommendation. CoRR Erdem Biyik, Fan Yao, Yinlam Chow, Alex Haig, Chih-Wei Hsu, Mohammad Ghavamzadeh, Craig Boutilier
2022	J	`jnl`	A Mixture-of-Expert Approach to RL-based Dialogue Management. CoRR Yinlam Chow, Aza Tulepbergenov, Ofir Nachum, Moonkyung Ryu, Mohammad Ghavamzadeh, Craig Boutilier
2022	A*	`conf`	Discovering Personalized Semantics for Soft Attributes in Recommender Systems using Concept Activation Vectors. WWW Christina Göpfert, Yinlam Chow, Chih-Wei Hsu, Ivan Vendrov, Tyler Lu, Deepak Ramachandran, Craig Boutilier
2022	J	`jnl`	Discovering Personalized Semantics for Soft Attributes in Recommender Systems using Concept Activation Vectors. CoRR Christina Göpfert, Yinlam Chow, Chih-Wei Hsu, Ivan Vendrov, Tyler Lu, Deepak Ramachandran, Craig Boutilier
2022	J	`jnl`	Dynamic Planning in Open-Ended Dialogue using Reinforcement Learning. CoRR Deborah Cohen, Moonkyung Ryu, Yinlam Chow, Orgad Keller, Ido Greenberg, Avinatan Hassidim, Michael Fink, Yossi Matias, Idan Szpektor, Craig Boutilier, Gal Elidan
2022	A*	`conf`	Efficient Risk-Averse Reinforcement Learning. NeurIPS Ido Greenberg, Yinlam Chow, Mohammad Ghavamzadeh, Shie Mannor
2022	J	`jnl`	Efficient Risk-Averse Reinforcement Learning. CoRR Ido Greenberg, Yinlam Chow, Mohammad Ghavamzadeh, Shie Mannor
2022	J	`jnl`	SAFER: Data-Efficient and Safe Reinforcement Learning via Skill Acquisition. CoRR Dylan Slack, Yinlam Chow, Bo Dai, Nevan Wichers
2021	A*	`conf`	Control-Aware Representations for Model-based Reinforcement Learning. ICLR Brandon Cui, Yinlam Chow, Mohammad Ghavamzadeh
2021	A	`conf`	Non-Stationary Off-Policy Optimization. AISTATS Joey Hong, Branislav Kveton, Manzil Zaheer, Yinlam Chow, Amr Ahmed
2021	A*	`conf`	Safe Reinforcement Learning with Natural Language Constraints. NeurIPS Tsung-Yen Yang, Michael Y. Hu, Yinlam Chow, Peter J. Ramadge, Karthik Narasimhan
2021	A*	`conf`	Variational Model-based Policy Optimization. IJCAI Yinlam Chow, Brandon Cui, Moonkyung Ryu, Mohammad Ghavamzadeh
2020	A*	`conf`	BRPO: Batch Residual Policy Optimization. IJCAI Sungryull Sohn, Yinlam Chow, Jayden Ooi, Ofir Nachum, Honglak Lee, Ed H. Chi, Craig Boutilier
2020	J	`jnl`	BRPO: Batch Residual Policy Optimization. CoRR Sungryull Sohn, Yinlam Chow, Jayden Ooi, Ofir Nachum, Honglak Lee, Ed H. Chi, Craig Boutilier
2020	A*	`conf`	CAQL: Continuous Action Q-Learning. ICLR Moonkyung Ryu, Yinlam Chow, Ross Anderson, Christian Tjandraatmadja, Craig Boutilier
2020	A*	`conf`	CoinDICE: Off-Policy Confidence Interval Estimation. NeurIPS Bo Dai, Ofir Nachum, Yinlam Chow, Lihong Li, Csaba Szepesvári, Dale Schuurmans
2020	J	`jnl`	CoinDICE: Off-Policy Confidence Interval Estimation. CoRR Bo Dai, Ofir Nachum, Yinlam Chow, Lihong Li, Csaba Szepesvári, Dale Schuurmans
2020	J	`jnl`	Control-Aware Representations for Model-based Reinforcement Learning. CoRR Brandon Cui, Yinlam Chow, Mohammad Ghavamzadeh
2020	A*	`conf`	Latent Bandits Revisited. NeurIPS Joey Hong, Branislav Kveton, Manzil Zaheer, Yinlam Chow, Amr Ahmed, Craig Boutilier
2020	J	`jnl`	Latent Bandits Revisited. CoRR Joey Hong, Branislav Kveton, Manzil Zaheer, Yinlam Chow, Amr Ahmed, Craig Boutilier
2020	J	`jnl`	Non-Stationary Latent Bandits. CoRR Joey Hong, Branislav Kveton, Manzil Zaheer, Yinlam Chow, Amr Ahmed, Mohammad Ghavamzadeh, Craig Boutilier
2020	J	`jnl`	Piecewise-Stationary Off-Policy Optimization. CoRR Joey Hong, Branislav Kveton, Manzil Zaheer, Yinlam Chow, Amr Ahmed
2020	A*	`conf`	Prediction, Consistency, Curvature: Representation Learning for Locally-Linear Control. ICLR Nir Levine, Yinlam Chow, Rui Shu, Ang Li, Mohammad Ghavamzadeh, Hung Bui
2020	A*	`conf`	Predictive Coding for Locally-Linear Control. ICML Rui Shu, Tung Nguyen, Yinlam Chow, Tuan Pham, Khoat Than, Mohammad Ghavamzadeh, Stefano Ermon, Hung H. Bui
2020	J	`jnl`	Predictive Coding for Locally-Linear Control. CoRR Rui Shu, Tung Nguyen, Yinlam Chow, Tuan Pham, Khoat Than, Mohammad Ghavamzadeh, Stefano Ermon, Hung H. Bui
2020	Misc	`conf`	Safe Policy Learning for Continuous Control. CoRL Yinlam Chow, Ofir Nachum, Aleksandra Faust, Edgar A. Duéñez-Guzmán, Mohammad Ghavamzadeh
2020	J	`jnl`	Safe Reinforcement Learning with Natural Language Constraints. CoRR Tsung-Yen Yang, Michael Y. Hu, Yinlam Chow, Peter J. Ramadge, Karthik Narasimhan
2020	J	`jnl`	Variational Model-based Policy Optimization. CoRR Yinlam Chow, Brandon Cui, Moonkyung Ryu, Mohammad Ghavamzadeh
2019	J	`jnl`	A Framework for Time-Consistent, Risk-Sensitive Model Predictive Control: Theory and Algorithms. IEEE Trans. Autom. Control. Sumeet Singh, Yinlam Chow, Anirudha Majumdar, Marco Pavone
2019	J	`jnl`	AlgaeDICE: Policy Gradient from Arbitrary Experience. CoRR Ofir Nachum, Bo Dai, Ilya Kostrikov, Yinlam Chow, Lihong Li, Dale Schuurmans
2019	J	`jnl`	CAQL: Continuous Action Q-Learning. CoRR Moonkyung Ryu, Yinlam Chow, Ross Anderson, Christian Tjandraatmadja, Craig Boutilier
2019	A*	`conf`	DualDICE: Behavior-Agnostic Estimation of Discounted Stationary Distribution Corrections. NeurIPS Ofir Nachum, Yinlam Chow, Bo Dai, Lihong Li
2019	J	`jnl`	DualDICE: Behavior-Agnostic Estimation of Discounted Stationary Distribution Corrections. CoRR Ofir Nachum, Yinlam Chow, Bo Dai, Lihong Li
2019	J	`jnl`	Lyapunov-based Safe Policy Optimization for Continuous Control. CoRR Yinlam Chow, Ofir Nachum, Aleksandra Faust, Mohammad Ghavamzadeh, Edgar A. Duéñez-Guzmán
2019	J	`jnl`	Prediction, Consistency, Curvature: Representation Learning for Locally-Linear Control. CoRR Nir Levine, Yinlam Chow, Rui Shu, Ang Li, Mohammad Ghavamzadeh, Hung Bui
2019	A	`conf`	Risk-Sensitive Generative Adversarial Imitation Learning. AISTATS Jonathan Lacotte, Mohammad Ghavamzadeh, Yinlam Chow, Marco Pavone
2018	A*	`conf`	A Block Coordinate Ascent Algorithm for Mean-Variance Optimization. NeurIPS Tengyang Xie, Bo Liu, Yangyang Xu, Mohammad Ghavamzadeh, Yinlam Chow, Daoming Lyu, Daesub Yoon
2018	J	`jnl`	A Block Coordinate Ascent Algorithm for Mean-Variance Optimization. CoRR Bo Liu, Tengyang Xie, Yangyang Xu, Mohammad Ghavamzadeh, Yinlam Chow, Daoming Lyu, Daesub Yoon
2018	A*	`conf`	A Lyapunov-based Approach to Safe Reinforcement Learning. NeurIPS Yinlam Chow, Ofir Nachum, Edgar A. Duéñez-Guzmán, Mohammad Ghavamzadeh
2018	J	`jnl`	A Lyapunov-based Approach to Safe Reinforcement Learning. CoRR Yinlam Chow, Ofir Nachum, Edgar A. Duéñez-Guzmán, Mohammad Ghavamzadeh
2018	—	`conf`	Imitation Learning from Visual Data with Multiple Intentions. ICLR (Poster) Aviv Tamar, Khashayar Rohanimanesh, Yinlam Chow, Chris Vigorito, Ben Goodrich, Michael Kahane, Derik Pridmore
2018	A*	`conf`	More Robust Doubly Robust Off-policy Evaluation. ICML Mehrdad Farajtabar, Yinlam Chow, Mohammad Ghavamzadeh
2018	J	`jnl`	More Robust Doubly Robust Off-policy Evaluation. CoRR Mehrdad Farajtabar, Yinlam Chow, Mohammad Ghavamzadeh
2018	A*	`conf`	Path Consistency Learning in Tsallis Entropy Regularized MDPs. ICML Yinlam Chow, Ofir Nachum, Mohammad Ghavamzadeh
2018	J	`jnl`	Path Consistency Learning in Tsallis Entropy Regularized MDPs. CoRR Ofir Nachum, Yinlam Chow, Mohammad Ghavamzadeh
2018	J	`jnl`	Risk-Sensitive Generative Adversarial Imitation Learning. CoRR Jonathan Lacotte, Yinlam Chow, Mohammad Ghavamzadeh, Marco Pavone
2017	J	`jnl`	Risk-Constrained Reinforcement Learning with Percentile Risk Criteria. J. Mach. Learn. Res. Yinlam Chow, Mohammad Ghavamzadeh, Lucas Janson, Marco Pavone
2017	J	`jnl`	Sequential Decision Making With Coherent Risk. IEEE Trans. Autom. Control. Aviv Tamar, Yinlam Chow, Mohammad Ghavamzadeh, Shie Mannor
2017	A	`conf`	Sequential Multiple Hypothesis Testing with Type I Error Control. AISTATS Alan Malek, Sumeet Katariya, Yinlam Chow, Mohammad Ghavamzadeh
2016	J	`jnl`	Distributed Online Modified Greedy Algorithm for Networked Storage Operation Under Uncertainty. IEEE Trans. Smart Grid Junjie Qin, Yinlam Chow, Jiyan Yang, Ram Rajagopal
2016	A*	`conf`	Risk aversion in finite Markov Decision Processes using total cost criteria and average value at risk. ICRA Stefano Carpin, Yinlam Chow, Marco Pavone
2016	—	`conf`	Safe Policy Improvement by Minimizing Robust Baseline Regret. NIPS Mohammad Ghavamzadeh, Marek Petrik, Yinlam Chow
2016	A*	`conf`	Weighted SGD for SODA Jiyan Yang, Yinlam Chow, Christopher Ré, Michael W. Mahoney
2015	—	`conf`	Policy Gradient for Coherent Risk Measures. NIPS Aviv Tamar, Yinlam Chow, Mohammad Ghavamzadeh, Shie Mannor
2015	J	`jnl`	Policy Gradient for Coherent Risk Measures. CoRR Aviv Tamar, Yinlam Chow, Mohammad Ghavamzadeh, Shie Mannor
2015	A	`conf`	Real-time Bidding based Vehicle Sharing. AAMAS Yinlam Chow, Jia Yuan Yu
2015	J	`jnl`	Real-time Bidding based Vehicle Sharing. CoRR Yinlam Chow, Jia Yuan Yu
2015	J	`jnl`	Risk-Constrained Reinforcement Learning with Percentile Risk Criteria. CoRR Yinlam Chow, Mohammad Ghavamzadeh, Lucas Janson, Marco Pavone
2015	—	`conf`	Risk-Sensitive and Robust Decision-Making: a CVaR Optimization Approach. NIPS Yinlam Chow, Aviv Tamar, Shie Mannor, Marco Pavone
2015	J	`jnl`	Risk-Sensitive and Robust Decision-Making: a CVaR Optimization Approach. CoRR Yinlam Chow, Aviv Tamar, Shie Mannor, Marco Pavone
2015	J	`jnl`	Trading Safety Versus Performance: Rapid Deployment of Robotic Swarms with Robust Performance Constraints. CoRR Yinlam Chow, Marco Pavone, Brian M. Sadler, Stefano Carpin
2014	—	`conf`	Algorithms for CVaR Optimization in MDPs. NIPS Yinlam Chow, Mohammad Ghavamzadeh
2014	J	`jnl`	Algorithms for CVaR Optimization in MDPs. CoRR Yinlam Chow, Mohammad Ghavamzadeh
2014	—	`conf`	Modeling and online control of generalized energy storage networks. e-Energy Junjie Qin, Yinlam Chow, Jiyan Yang, Ram Rajagopal
2014	—	`conf`	Weighted difference approximation of value functions for slow-discounting Markov Decision Processes. CDC Yinlam Chow, Junjie Qin