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Gene Li
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Conference and Workshop Papers
- 2024
- [c7]Avrim Blum, Meghal Gupta, Gene Li, Naren Sarayu Manoj, Aadirupa Saha, Yuanyuan Yang:
Dueling Optimization with a Monotone Adversary. ALT 2024: 221-243 - [c6]Gene Li, Lin Chen, Adel Javanmard, Vahab Mirrokni:
Optimistic Rates for Learning from Label Proportions. COLT 2024: 3437-3474 - 2023
- [c5]Zeyu Jia, Gene Li, Alexander Rakhlin, Ayush Sekhari, Nati Srebro:
When is Agnostic Reinforcement Learning Statistically Tractable? NeurIPS 2023 - 2022
- [c4]Gene Li, Pritish Kamath, Dylan J. Foster, Nati Srebro:
Understanding the Eluder Dimension. NeurIPS 2022 - [c3]Gene Li, Junbo Li, Anmol Kabra, Nati Srebro, Zhaoran Wang, Zhuoran Yang:
Exponential Family Model-Based Reinforcement Learning via Score Matching. NeurIPS 2022 - [c2]Gene Li, Cong Ma, Nati Srebro:
Pessimism for Offline Linear Contextual Bandits using $\ell_p$ Confidence Sets. NeurIPS 2022 - 2015
- [c1]Gene Li:
Specialty technology for loT. VLSI-DAT 2015: 1
Informal and Other Publications
- 2024
- [i6]Gene Li, Lin Chen, Adel Javanmard, Vahab Mirrokni:
Optimistic Rates for Learning from Label Proportions. CoRR abs/2406.00487 (2024) - 2023
- [i5]Zeyu Jia, Gene Li, Alexander Rakhlin, Ayush Sekhari, Nathan Srebro:
When is Agnostic Reinforcement Learning Statistically Tractable? CoRR abs/2310.06113 (2023) - [i4]Avrim Blum, Meghal Gupta, Gene Li, Naren Sarayu Manoj, Aadirupa Saha, Yuanyuan Yang:
Dueling Optimization with a Monotone Adversary. CoRR abs/2311.11185 (2023) - 2022
- [i3]Gene Li, Cong Ma, Nathan Srebro:
Pessimism for Offline Linear Contextual Bandits using 𝓁p Confidence Sets. CoRR abs/2205.10671 (2022) - 2021
- [i2]Gene Li, Pritish Kamath, Dylan J. Foster, Nathan Srebro:
Eluder Dimension and Generalized Rank. CoRR abs/2104.06970 (2021) - [i1]Gene Li, Junbo Li, Nathan Srebro, Zhaoran Wang, Zhuoran Yang:
Exponential Family Model-Based Reinforcement Learning via Score Matching. CoRR abs/2112.14195 (2021)
Coauthor Index
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