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Towards Demystifying Representation Learning with Non-contrastive Self-supervision


Oct 11, 2021
Xiang Wang, Xinlei Chen, Simon S. Du, Yuandong Tian


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Multi-objective Optimization by Learning Space Partitions


Oct 10, 2021
Yiyang Zhao, Linnan Wang, Kevin Yang, Tianjun Zhang, Tian Guo, Yuandong Tian


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CompilerGym: Robust, Performant Compiler Optimization Environments for AI Research


Sep 17, 2021
Chris Cummins, Bram Wasti, Jiadong Guo, Brandon Cui, Jason Ansel, Sahir Gomez, Somya Jain, Jia Liu, Olivier Teytaud, Benoit Steiner, Yuandong Tian, Hugh Leather

* 12 pages. Source code available at https://github.com/facebookresearch/CompilerGym 

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Learning Space Partitions for Path Planning


Jul 14, 2021
Kevin Yang, Tianjun Zhang, Chris Cummins, Brandon Cui, Benoit Steiner, Linnan Wang, Joseph E. Gonzalez, Dan Klein, Yuandong Tian


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Latent Execution for Neural Program Synthesis Beyond Domain-Specific Languages


Jun 29, 2021
Xinyun Chen, Dawn Song, Yuandong Tian


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MADE: Exploration via Maximizing Deviation from Explored Regions


Jun 18, 2021
Tianjun Zhang, Paria Rashidinejad, Jiantao Jiao, Yuandong Tian, Joseph Gonzalez, Stuart Russell

* 28 pages, 10 figures 

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Understanding Robustness in Teacher-Student Setting: A New Perspective


Mar 01, 2021
Zhuolin Yang, Zhaoxi Chen, Tiffany Cai, Xinyun Chen, Bo Li, Yuandong Tian

* Proceedings of the 24th International Conference on Artificial Intelligence and Statistics (AISTATS) 2021, San Diego, California, USA. PMLR: Volume 130 

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Provably Efficient Policy Gradient Methods for Two-Player Zero-Sum Markov Games


Feb 17, 2021
Yulai Zhao, Yuandong Tian, Jason D. Lee, Simon S. Du


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Understanding self-supervised Learning Dynamics without Contrastive Pairs


Feb 12, 2021
Yuandong Tian, Xinlei Chen, Surya Ganguli


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BeBold: Exploration Beyond the Boundary of Explored Regions


Dec 15, 2020
Tianjun Zhang, Huazhe Xu, Xiaolong Wang, Yi Wu, Kurt Keutzer, Joseph E. Gonzalez, Yuandong Tian


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FP-NAS: Fast Probabilistic Neural Architecture Search


Nov 24, 2020
Zhicheng Yan, Xiaoliang Dai, Peizhao Zhang, Yuandong Tian, Bichen Wu, Matt Feiszli


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Understanding Self-supervised Learning with Dual Deep Networks


Oct 22, 2020
Yuandong Tian, Lantao Yu, Xinlei Chen, Surya Ganguli


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Multi-Agent Collaboration via Reward Attribution Decomposition


Oct 16, 2020
Tianjun Zhang, Huazhe Xu, Xiaolong Wang, Yi Wu, Kurt Keutzer, Joseph E. Gonzalez, Yuandong Tian


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Planning in Learned Latent Action Spaces for Generalizable Legged Locomotion


Sep 18, 2020
Tianyu Li, Roberto Calandra, Deepak Pathak, Yuandong Tian, Franziska Meier, Akshara Rai


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Real-world Video Adaptation with Reinforcement Learning


Aug 28, 2020
Hongzi Mao, Shannon Chen, Drew Dimmery, Shaun Singh, Drew Blaisdell, Yuandong Tian, Mohammad Alizadeh, Eytan Bakshy

* Reinforcement Learning for Real Life (RL4RealLife) Workshop in the 36th International Conference on Machine Learning, Long Beach, California, USA, 2019 

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Joint Policy Search for Multi-agent Collaboration with Imperfect Information


Aug 24, 2020
Yuandong Tian, Qucheng Gong, Tina Jiang


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Learning Search Space Partition for Black-box Optimization using Monte Carlo Tree Search


Jul 01, 2020
Linnan Wang, Rodrigo Fonseca, Yuandong Tian


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Towards Automated Neural Interaction Discovery for Click-Through Rate Prediction


Jun 29, 2020
Qingquan Song, Dehua Cheng, Hanning Zhou, Jiyan Yang, Yuandong Tian, Xia Hu


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Few-shot Neural Architecture Search


Jun 19, 2020
Yiyang Zhao, Linnan Wang, Yuandong Tian, Rodrigo Fonseca, Tian Guo


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FBNetV3: Joint Architecture-Recipe Search using Neural Acquisition Function


Jun 07, 2020
Xiaoliang Dai, Alvin Wan, Peizhao Zhang, Bichen Wu, Zijian He, Zhen Wei, Kan Chen, Yuandong Tian, Matthew Yu, Peter Vajda, Joseph E. Gonzalez


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