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Dean Foster
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2020 – today
- 2023
- [c6]Dean Foster, Dylan J. Foster, Noah Golowich, Alexander Rakhlin:
On the Complexity of Multi-Agent Decision Making: From Learning in Games to Partial Monitoring. COLT 2023: 2678-2792 - [i4]Hanlin Zhang, Yi-Fan Zhang, Yaodong Yu, Dhruv Madeka, Dean Foster, Eric P. Xing, Himabindu Lakkaraju, Sham M. Kakade:
A Study on the Calibration of In-context Learning. CoRR abs/2312.04021 (2023) - [i3]Xinyi Chen, Angelica Chen, Dean Foster, Elad Hazan:
AI safety by debate via regret minimization. CoRR abs/2312.04792 (2023) - 2021
- [c5]Yucheng Lu, Youngsuk Park, Lifan Chen, Yuyang Wang, Christopher De Sa, Dean Foster:
Variance Reduced Training with Stratified Sampling for Forecasting Models. ICML 2021: 7145-7155 - [c4]Rajat Sen, Alexander Rakhlin, Lexing Ying, Rahul Kidambi, Dean Foster, Daniel N. Hill, Inderjit S. Dhillon:
Top-k eXtreme Contextual Bandits with Arm Hierarchy. ICML 2021: 9422-9433 - [i2]Yucheng Lu, Youngsuk Park, Lifan Chen, Yuyang Wang, Christopher De Sa, Dean Foster:
Variance Reduction in Training Forecasting Models with Subgroup Sampling. CoRR abs/2103.02062 (2021)
2010 – 2019
- 2019
- [c3]Yuyang Wang, Alex Smola, Danielle C. Maddix, Jan Gasthaus, Dean Foster, Tim Januschowski:
Deep Factors for Forecasting. ICML 2019: 6607-6617 - [c2]Kyungjin Yoo, Dean Foster:
Interactive Visualization of Painting Data with Augmented Reality. VRST 2019: 76:1 - [c1]Kyungjin Yoo, Dean Foster:
Interactive Visualization of Painting Data with Augmented Reality. VRST 2019: 110:1-110:2 - [i1]Yuyang Wang, Alex Smola, Danielle C. Maddix, Jan Gasthaus, Dean Foster, Tim Januschowski:
Deep Factors for Forecasting. CoRR abs/1905.12417 (2019)
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