Yuandong Tian's webpage

	Searching Large Neighborhoods for Integer Linear Programs with Contrastive Learning [link] Taoan Huang, Aaron Ferber, Yuandong Tian, Bistra Dilkina, Benoit Steiner arXiv 2023
	Learning Compiler Pass Orders using Coreset and Normalized Value Prediction [link] Youwei Liang, Kevin Stone, Ali Shameli, Chris Cummins, Mostafa Elhoushi, Jiadong Guo, Benoit Steiner, Xiaomeng Yang, Pengtao Xie, Hugh Leather, Yuandong Tian (* = Equal 1st authors) arXiv 2023
	Local Branching Relaxation Heuristics for Integer Linear Programs [link] Taoan Huang, Aaron Ferber, Yuandong Tian, Bistra Dilkina, Benoit Steiner CPAIOR 2023
	Efficient Planning in a Compact Latent Action Space [link] [code] [website] Zhengyao Jiang, Tianjun Zhang, Michael Janner, Yueying Li, Tim Rocktäschel, Edward Grefenstette, Yuandong Tian ICLR 2023
	Understanding the Role of Nonlinearity in Training Dynamics of Contrastive Learning [link] [code] [workshop version] [workshop poster] Yuandong Tian ICLR 2023
	MACTA: A Multi-agent Reinforcement Learning Approach for Cache Timing Attacks and Detection [link] Jiaxun Cui, Xiaomeng Yang, Geunbae Lee, Mulong Luo, Peter Stone, Hsien-Hsin S. Lee, Benjamin Lee, G. Edward Suh, Wenjie Xiong, Yuandong Tian* (* = Equal 2nd authors, ** = Equal advising) ICLR 2023
	Modeling Scattering Coefficients using Self-Attentive Complex Polynomials with Image-based Representation [link] Andrew Cohen, Weiping Dou, Jiang Zhu, Slawomir Koziel, Peter Renner, Jan-Ove Mattsson, Xiaomeng Yang, Beidi Chen, Kevin Stone, Yuandong Tian (* = Equal 1st authors) arXiv 2023
	DOC: Improving Long Story Coherence With Detailed Outline Control [link] [code] Kevin Yang, Dan Klein, Nanyun Peng, Yuandong Tian arXiv 2022
	SurCo: Learning Linear Surrogates For Combinatorial Nonlinear Optimization Problems [link] [Slides] Aaron Ferber, Taoan Huang, Daochen Zha, Martin Schubert, Benoit Steiner, Bistra Dilkina, Yuandong Tian arXiv 2022
	AutoCAT: Reinforcement Learning for Automated Exploration of Cache Timing-Channel Attacks [link] [code] Mulong Luo, Wenjie Xiong, Geunbae Lee, Yueying Li, Xiaomeng Yang, Amy Zhang, Yuandong Tian, Hsien Hsin S Lee, G Edward Suh (* = Equal 1st authors) HPCA 2023
	Re3: Generating Longer Stories With Recursive Reprompting and Revision [link] [code] Kevin Yang, Yuandong Tian, Nanyun Peng, Dan Klein EMNLP 2022
	Understanding Deep Contrastive Learning via Coordinate-wise Optimization [link] [code] [video] [5min talk slides] [poster] Yuandong Tian NeurIPS 2022 *(Oral)*
	DreamShard: Generalizable Embedding Table Placement for Recommender Systems [link] [code] Daochen Zha, Louis Feng, Qiaoyu Tan, Zirui Liu, Kwei-Herng Lai, Bhargav Bhushanam, Yuandong Tian, Arun Kejariwal, Xia Hu NeurIPS 2022
	AutoShard: Automated Embedding Table Sharding for Recommender Systems [link] [code] Daochen Zha, Louis Feng, Bhargav Bhushanam, Dhruv Choudhary, Jade Nie, Yuandong Tian, Jay Chae, Yinbin Ma, Arun Kejariwal, Xia Hu KDD 2022
	Denoised MDPs: Learning World Models Better Than the World Itself [link] [code] [website] Tongzhou Wang, Simon S Du, Antonio Torralba, Phillip Isola, Amy Zhang, Yuandong Tian ICML 2022
	On the Importance of Asymmetry for Siamese Representation Learning [link] [code] Xiao Wang, Haoqi Fan, Yuandong Tian, Daisuke Kihara, Xinlei Chen (* = Equal 1st authors) CVPR 2022
	Understanding Dimensional Collapse in Contrastive Self-supervised Learning [link] [code] Li Jing, Pascal Vincent, Yann LeCun, Yuandong Tian ICLR 2022
	NASViT: Neural Architecture Search for Efficient Vision Transformers with Gradient Conflict aware Supernet Training [link] [code] Chengyue Gong, Dilin Wang, Meng Li, Xinlei Chen, Zhicheng Yan, Yuandong Tian, Vikas Chandra ICLR 2022
	Multi-objective Optimization by Learning Space Partitions [link] [code] Yiyang Zhao, Linnan Wang, Kevin Yang, Tianjun Zhang, Tian Guo, Yuandong Tian ICLR 2022
	Towards demystifying representation learning with non-contrastive self-supervision [link] Xiang Wang, Xinlei Chen, Simon S Du, Yuandong Tian arXiv 2021
	Sample-Efficient Neural Architecture Search by Learning Action Space [link] [code] Linnan Wang, Saining Xie, Teng Li, Rodrigo Fonseca, Yuandong Tian T-PAMI 2021
	Learning Bounded Context-Free-Grammar via LSTM and the Transformer: Difference and Explanations [link] [code] Hui Shi, Sicun Gao, Yuandong Tian, Xinyun Chen, Jishen Zhao AAAI 2022
	CompilerGym: robust, performant compiler optimization environments for AI research [link] [code] Chris Cummins, Bram Wasti, Jiadong Guo, Brandon Cui, Jason Ansel, Sahir Gomez, Somya Jain, Jia Liu, Olivier Teytaud, Benoit Steiner, Yuandong Tian, Hugh Leather CGO 2022 *(Outstanding Paper)*
	NovelD: A Simple yet Effective Exploration Criterion [link] [code] [video] Tianjun Zhang, Huazhe Xu, Xiaolong Wang, Yi Wu, Kurt Keutzer, Joseph E. Gonzalez, Yuandong Tian NeurIPS 2021
	MADE: Exploration via Maximizing Deviation from Explored Regions [link] [code] Tianjun Zhang, Paria Rashidinejad, Jiantao Jiao, Yuandong Tian, Joseph Gonzalez, Stuart Russell (* = Equal 1st authors) NeurIPS 2021
	Learning Space Partitions for Path Planning [link] [code] Kevin Yang, Tianjun Zhang, Chris Cummins, Brandon Cui, Benoit Steiner, Linnan Wang, Joseph E. Gonzalez, Dan Klein, Yuandong Tian (* = Equal 1st authors) NeurIPS 2021
	Latent Execution for Neural Program Synthesis Beyond Domain-Specific Languages [link] [code] Xinyun Chen, Dawn Song, Yuandong Tian NeurIPS 2021
	Understanding Self-supervised Learning Dynamics without Contrastive Pairs [link] [code] [video] [Slides] [Blogpost] Yuandong Tian, Xinlei Chen, Surya Ganguli ICML 2021 *(Outstanding Paper Award Honorable Mention)*
	Few-shot Neural Architecture Search [link] [code] [Blogpost] Yiyang Zhao, Linnan Wang, Yuandong Tian, Rodrigo Fonseca, Tian Guo (* = Equal 1st authors) ICML 2021 *(Long Oral)*
	Learn-to-Share: A Hardware-friendly Transfer Learning Framework Exploiting Computation and Parameter Sharing [link] Cheng Fu, Hanxian Huang, Xinyun Chen, Yuandong Tian, Jishen Zhao (UCSD) ICML 2021 *(Long Oral)*
	Network Planning with Deep Reinforcement Learning [link] [code] Hang Zhu (JHU), Varun Gupta, Satyajeet Singh Ahuja, Yuandong Tian, Ying Zhang, Xin Jin SIGCOMM 2021
	FBNetV3: Joint Architecture-Recipe Search using Predictor Pretraining [link] Xiaoliang Dai, Alvin Wan, Peizhao Zhang, Bichen Wu, Zijian He, Zhen Wei, Kan Chen, Yuandong Tian, Matthew Yu, Peter Vajda, Joseph Gonzalez CVPR 2021
	FPNAS: Fast Probabilistic Neural Architecture Search [link] Zhicheng Yan, Xiaoliang Dai, Peizhao Zhang, Yuandong Tian, Bichen Wu, Matt Feiszli CVPR 2021
	Understanding Robustness in Teacher-Student Setting: A New Perspective [link] [Slides] Zhuolin Yang, Zhaoxi Chen, Tiffany Cai, Xinyun Chen, Bo Li, Yuandong Tian (* = Equal 1st authors) AIStats 2021
	Multi-Agent Collaboration via Reward Attribution Decomposition [link] [code] [video] [website] Tianjun Zhang, Huazhe Xu, Xiaolong Wang, Yi Wu, Kurt Keutzer, Joseph E. Gonzalez, Yuandong Tian arxiv 2020
	Joint Policy Search for Multi-agent Collaboration with Imperfect Information [link] [code] [video] Yuandong Tian, Qucheng Gong, Tina Jiang NeurIPS 2020
	Understanding Self-supervised Learning with Dual Deep Networks [link] [code] [video] Yuandong Tian, Lantao Yu, Xinlei Chen, Surya Ganguli arXiv 2020
	Student Specialization in Deep ReLU Networks With Finite Width and Input Dimension [link] [code] Yuandong Tian ICML 2020
	Playing the lottery with rewards and multiple languages: lottery tickets in RL and NLP [link] Haonan Yu, Sergey Edunov, Yuandong Tian, Ari S. Morcos ICLR 2020
	Learning Search Space Partition for Black-box Optimization using Monte Carlo Tree Search [link] [code] Linnan Wang, Rodrigo Fonseca, Yuandong Tian NeurIPS 2020
	Towards Automated Neural Interaction Discovery for Click-Through Rate Prediction [link] Qingquan Song, Dehua Cheng, Hanning Zhou, Jiyan Yang, Yuandong Tian, Xia Hu KDD 2020
	FBNetV2: Differentiable Neural Architecture Search for Spatial and Channel Dimensions [link] [code] Alvin Wan, Xiaoliang Dai, Peizhao Zhang, Zijian He, Yuandong Tian, Saining Xie, Bichen Wu, Matthew Yu, Tao Xu, Kan Chen, Peter Vajda, Joseph Gonzalez CVPR 2020
	N-Bref : A High-fidelity Decompiler Exploiting Programming Structures [link] [code] [Blogpost] Cheng Fu, Kunlin Yang, Xinyun Chen, Yuandong Tian, Jishen Zhao arxiv 2020
	AlphaX: Exploring Neural Architectures with Deep Neural Networks and Monte Carlo Tree Search [link] Linnan Wang, Yiyang Zhao, Yuu Jinnai, Yuandong Tian, Rodrigo Fonseca AAAI 2020
	Deep Symbolic Superoptimization Without Human Knowledge [link] [code] Hui Shi, Yang Zhang, Xinyun Chen, Yuandong Tian, Jishen Zhao ICLR 2020
	Hierarchical Decision Making by Generating and Following Natural Language Instructions [link] [code] Hengyuan Hu, Denis Yarats, Qucheng Gong, Yuandong Tian, Mike Lewis (* = Equal 1st authors) NeurIPS 2019
	ELF OpenGo: An Analysis and Open Reimplementation of AlphaZero [link] [code] [pretrained model and game records] [Other resources] [Blogpost] [Talk] An open source reimplementation of DeepMind's zero-knowledge training and its application to the game of Go. Trained on 2000 GPUs for 9 days. With a single GPU and 50 seconds per move, the model won 20-0 versus 4 top 30 professional players, given human unlimited thinking time. It also won 980-18 versus LeelaZero (version Apr. 25). Yuandong Tian, Jerry Ma, Qucheng Gong, Shubho Sengupta, Zhuoyuan Chen, James Pinkerton, Larry Zitnick ( = Equal 2nd authors) ICML 2019 *(Long Oral)*
	Algorithmic Framework for Model-based Deep Reinforcement Learning with Theoretical Guarantees [link] [code] Yuping Luo, Huazhe Xu, Yuanzhi Li, Yuandong Tian, Trevor Darrell, Tengyu Ma (* = Equal 1st authors) ICLR 2019
	M^3RL: Mind-aware Multi-agent Management Reinforcement Learning [link] [code] Tianmin Shu, Yuandong Tian ICLR 2019
	Luck Matters: Understanding Training Dynamics of Deep ReLU Networks [link] [code] [Poster] Yuandong Tian, Tina Jiang, Qucheng Gong, Ari Morcos ICML-workshop 2019
	One ticket to win them all: generalizing lottery ticket initializations across datasets and optimizers [link] Ari S. Morcos, Haonan Yu, Michela Paganini, Yuandong Tian NeurIPS 2019
	Real-world video adaptation with reinforcement learning [link] Hongzi Mao, Shannon Chen, Drew Dimmery, Shaun Singh, Drew Blaisdell, Yuandong Tian, Mohammad Alizadeh, Eytan Bakshy ICML-Workshop 2019
	FBNet: Hardware-Aware Efficient ConvNet Design via Differentiable Neural Architecture Search [link] [code] Bichen Wu, Xiaoliang Dai, Peizhao Zhang, Yanghan Wang, Fei Sun, Yiming Wu, Yuandong Tian, Peter Vajda, Yangqing Jia, Kurt Keutzer CVPR 2019
	Learning to Perform Local Rewriting for Combinatorial Optimization [link] [code] Xinyun Chen, Yuandong Tian NeurIPS 2019
	Coda: An End-to-End Neural Program Decompiler [link] Cheng Fu, Huili Chen, Haolan Liu, Xinyun Chen, Yuandong Tian, Farinaz Koushanfar, Jishen Zhao NeurIPS 2019
	Building Generalizable Agents with a Realistic and Rich 3D Environment [link] [code] Yi Wu, Yuxin Wu, Georgia Gkioxari, Yuandong Tian ICLR-Workshop 2018
	A Theoretical Framework for Deep Locally Connected ReLU Network [link] [Poster] Yuandong Tian arxiv 2018
	Gradient Descent Learns One-hidden-layer CNN: Don't be Afraid of Spurious Local Minima [link] Simon S. Du, Jason D. Lee, Yuandong Tian, Barnabas Poczos, Aarti Singh ICML 2018 *(Long Oral)*
	When is a Convolutional Filter Easy To Learn? [link] Simon S. Du, Jason D. Lee, Yuandong Tian ICLR 2018
	ELF: An Extensive, Lightweight and Flexible Research Platform for Real-time Strategy Games [link] [code] [video] Yuandong Tian, Qucheng Gong, Wenling Shang, Yuxin Wu, Larry Zitnick NeurIPS 2017 *(Oral)*
	Training Agent for First-Person Shooter Game with Actor-Critic Curriculum Learning [link] Yuxin Wu, Yuandong Tian ICLR 2017
	An Analytical Formula of Population Gradient for two-layered ReLU network and its Applications in Convergence and Critical Point Analysis [link] [code] Yuandong Tian ICML 2017
	Semantic Amodal Segmentation [link] Yan Zhu, Yuandong Tian, Dimitris Mexatas, Piotr Dollár CVPR 2017
	Better Computer Go Player with Neural Network and Long-term Prediction [link] [code] [pretrained model] [mit tech review] Yuandong Tian, Yan Zhu ICLR 2016
	Single Image 3D Interpreter Network [link] Jiajun Wu, Tianfan Xue, Joseph J. Lim, Yuandong Tian, Joshua B. Tenenbaum, Antonio Torralba, William T. Freeman (* = Equal 1st authors) ECCV 2016 *(Oral)*
	Simple Baseline for Visual Question Answering [link] [code] Bolei Zhou, Yuandong Tian, Sainbayar Sukhbaatar, Arthur Szlam, Rob Fergus arxiv 2016
	Theory and Practice of Hierarchical Data-driven Descent for Optimal Deformation Estimation [link] Yuandong Tian, Srinivasa G. Narasimhan IJCV 2015
	Theory and Practice of Globally Optimal Deformation Estimation [link] Yuandong Tian PhD thesis 2013
	Hierarchical Data-Driven Descent for Efficient Optimal Deformation Estimation [link] [Proofs] Yuandong Tian, Srinivasa G. Narasimhan ICCV 2013 *(Marr Prize Honorable Mentions)*
	Integrating Perceptual Learning with External World Knowledge in a Simulated Student [link] Nan Li, Yuandong Tian, William W. Cohen, Ken Koedinger AIED 2013
	Exploring the Spatial Hierarchy of Mixture Models for Human Pose Estimation [link] [code] [website] Yuandong Tian, Larry Zitnick, Srinivasa G. Narasimhan ECCV 2012
	Learning from Crowds in the Presence of Schools of Thought [link] [code] [Slides] [Dataset] Yuandong Tian, Jun Zhu KDD 2012
	Depth from Optical Turbulence [link] [website] Yuandong Tian, Srinivasa G. Narasimhan, Alan J. Vannevel CVPR 2012
	A Combined Theory of Defocused Illumination and Global Light Transport [link] Mohit Gupta, Yuandong Tian, Srinivasa G. Narasimhan, Li Zhang IJCV 2011
	Globally Optimal Estimation of Nonrigid Image Distortion [link] Yuandong Tian, Srinivasa G. Narasimhan IJCV 2011
	Rectification and 3D reconstruction of Curved Document Images [link] [website] Yuandong Tian, Srinivasa G. Narasimhan CVPR 2011 *(Oral)*
	Local Isomorphism to Solve the Pre-image Problem in Kernel Methods [link] Dong Huang, Yuandong Tian, Fernando De la Torre CVPR 2011
	A Globally Optimal Data-Driven Approach for Image Distortion Estimation [link] [website] Yuandong Tian, Srinivasa G. Narasimhan CVPR 2010 *(Oral)*
	Seeing through water: Image restoration using model-based tracking [link] [website] Yuandong Tian, Srinivasa G. Narasimhan ICCV 2009
	(De) Focusing on Global Light Transport for Active Scene Recovery [link] Mohit Gupta, Yuandong Tian, Srinivasa G. Narasimhan, Li Zhang CVPR 2009 *(Oral)*

Brief Bio

News