Yinlam Chow
Publication record assembled from the DBLP archive of ranked conferences.
Papers indexed
20
Venues
8
Active years
2016–2025
Best venue rank
A*
Where they publish
Papers
20 indexed papers, newest first.
| Year | Venue | Title | Authors |
|---|---|---|---|
| 2025 | ICLR | Inference-Aware Fine-Tuning for Best-of-N Sampling in Large Language Models. | Yinlam Chow, Guy Tennenholtz, Izzeddin Gur, Vincent Zhuang, Bo Dai, Aviral Kumar, Rishabh Agarwal, Sridhar Thiagarajan, Craig Boutilier, Aleksandra Faust |
| 2025 | ICML | Preference Adaptive and Sequential Text-to-Image Generation. | Ofir Nabati, Guy Tennenholtz, Chih-Wei Hsu, Moonkyung Ryu, Deepak Ramachandran, Yinlam Chow, Xiang Li, Craig Boutilier |
| 2024 | ICLR | 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 |
| 2023 | ICLR | A Mixture-of-Expert Approach to RL-based Dialogue Management. | Yinlam Chow, Aza Tulepbergenov, Ofir Nachum, Dhawal Gupta, Moonkyung Ryu, Mohammad Ghavamzadeh, Craig Boutilier |
| 2022 | WWW | Discovering Personalized Semantics for Soft Attributes in Recommender Systems using Concept Activation Vectors. | Christina Gpfert, Yinlam Chow, Chih-Wei Hsu, Ivan Vendrov, Tyler Lu, Deepak Ramachandran, Craig Boutilier |
| 2021 | AISTATS | Non-Stationary Off-Policy Optimization. | Joey Hong, Branislav Kveton, Manzil Zaheer, Yinlam Chow, Amr Ahmed |
| 2021 | ICLR | Control-Aware Representations for Model-based Reinforcement Learning. | Brandon Cui, Yinlam Chow, Mohammad Ghavamzadeh |
| 2021 | IJCAI | Variational Model-based Policy Optimization. | Yinlam Chow, Brandon Cui, Moonkyung Ryu, Mohammad Ghavamzadeh |
| 2020 | CoRL | Safe Policy Learning for Continuous Control. | Yinlam Chow, Ofir Nachum, Aleksandra Faust, Edgar A. Duez-Guzmn, Mohammad Ghavamzadeh |
| 2020 | ICLR | Prediction, Consistency, Curvature: Representation Learning for Locally-Linear Control. | Nir Levine, Yinlam Chow, Rui Shu, Ang Li, Mohammad Ghavamzadeh, Hung Bui |
| 2020 | ICLR | CAQL: Continuous Action Q-Learning. | Moonkyung Ryu, Yinlam Chow, Ross Anderson, Christian Tjandraatmadja, Craig Boutilier |
| 2020 | ICML | Predictive Coding for Locally-Linear Control. | Rui Shu, Tung Nguyen, Yinlam Chow, Tuan Pham, Khoat Than, Mohammad Ghavamzadeh, Stefano Ermon, Hung H. Bui |
| 2020 | IJCAI | BRPO: Batch Residual Policy Optimization. | Sungryull Sohn, Yinlam Chow, Jayden Ooi, Ofir Nachum, Honglak Lee, Ed H. Chi, Craig Boutilier |
| 2019 | AISTATS | Risk-Sensitive Generative Adversarial Imitation Learning. | Jonathan Lacotte, Mohammad Ghavamzadeh, Yinlam Chow, Marco Pavone |
| 2018 | ICLR | Imitation Learning from Visual Data with Multiple Intentions. | Aviv Tamar, Khashayar Rohanimanesh, Yinlam Chow, Chris Vigorito, Ben Goodrich, Michael Kahane, Derik Pridmore |
| 2018 | ICML | Path Consistency Learning in Tsallis Entropy Regularized MDPs. | Yinlam Chow, Ofir Nachum, Mohammad Ghavamzadeh |
| 2018 | ICML | More Robust Doubly Robust Off-policy Evaluation. | Mehrdad Farajtabar, Yinlam Chow, Mohammad Ghavamzadeh |
| 2017 | AISTATS | Sequential Multiple Hypothesis Testing with Type I Error Control. | Alan Malek, Sumeet Katariya, Yinlam Chow, Mohammad Ghavamzadeh |
| 2016 | ICRA | Risk aversion in finite Markov Decision Processes using total cost criteria and average value at risk. | Stefano Carpin, Yinlam Chow, Marco Pavone |
| 2016 | SODA | Weighted SGD for | Jiyan Yang, Yinlam Chow, Christopher R, Michael W. Mahoney |