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ORCIDYuandong Tian
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- affiliation: Carnegie Mellon University
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2020 – today
- 2024
[c93]Zhengyao Jiang, Yingchen Xu, Nolan Wagener, Yicheng Luo, Michael Janner, Edward Grefenstette, Tim Rocktäschel, Yuandong Tian:
H-GAP: Humanoid Control with a Generalist Planner. ICLR 2024- [c92]Yuandong Tian, Yiping Wang, Zhenyu Zhang, Beidi Chen, Simon Shaolei Du:
JoMA: Demystifying Multilayer Transformers via Joint Dynamics of MLP and Attention. ICLR 2024 - [c91]Guangxuan Xiao, Yuandong Tian, Beidi Chen, Song Han, Mike Lewis:
Efficient Streaming Language Models with Attention Sinks. ICLR 2024 - [c90]Kevin Yang, Dan Klein, Asli Celikyilmaz, Nanyun Peng, Yuandong Tian:
RLCD: Reinforcement Learning from Contrastive Distillation for LM Alignment. ICLR 2024 - [c89]Ruisi Cai, Yuandong Tian, Zhangyang Wang, Beidi Chen:
LoCoCo: Dropping In Convolutions for Long Context Compression. ICML 2024 - [c88]Aaron M. Ferber, Arman Zharmagambetov, Taoan Huang, Bistra Dilkina, Yuandong Tian:
GenCO: Generating Diverse Designs with Combinatorial Constraints. ICML 2024 - [c87]Taoan Huang, Aaron M. Ferber, Arman Zharmagambetov, Yuandong Tian, Bistra Dilkina:
Contrastive Predict-and-Search for Mixed Integer Linear Programs. ICML 2024 - [c86]Zechun Liu, Changsheng Zhao, Forrest N. Iandola, Chen Lai, Yuandong Tian, Igor Fedorov, Yunyang Xiong, Ernie Chang, Yangyang Shi, Raghuraman Krishnamoorthi, Liangzhen Lai, Vikas Chandra:
MobileLLM: Optimizing Sub-billion Parameter Language Models for On-Device Use Cases. ICML 2024 - [c85]Jian Xie, Kai Zhang, Jiangjie Chen, Tinghui Zhu, Renze Lou, Yuandong Tian, Yanghua Xiao, Yu Su:
TravelPlanner: A Benchmark for Real-World Planning with Language Agents. ICML 2024 - [c84]Jiawei Zhao, Zhenyu Zhang, Beidi Chen, Zhangyang Wang, Anima Anandkumar, Yuandong Tian:
GaLore: Memory-Efficient LLM Training by Gradient Low-Rank Projection. ICML 2024 - [i99]Yang Zhong, Weiping Dou, Andrew Cohen, Dia'a Bisharat, Yuandong Tian, Jiang Zhu, Qing Huo Liu:
Image Classifier Based Generative Method for Planar Antenna Design. CoRR abs/2401.06149 (2024) - [i98]Jian Xie, Kai Zhang, Jiangjie Chen, Tinghui Zhu, Renze Lou, Yuandong Tian, Yanghua Xiao, Yu Su:
TravelPlanner: A Benchmark for Real-World Planning with Language Agents. CoRR abs/2402.01622 (2024) - [i97]Zihan Ding, Amy Zhang, Yuandong Tian, Qinqing Zheng:
Diffusion World Model. CoRR abs/2402.03570 (2024) - [i96]Lucas Lehnert, Sainbayar Sukhbaatar, Paul McVay, Michael Rabbat, Yuandong Tian:
Beyond A*: Better Planning with Transformers via Search Dynamics Bootstrapping. CoRR abs/2402.14083 (2024) - [i95]Zechun Liu, Changsheng Zhao, Forrest N. Iandola, Chen Lai, Yuandong Tian, Igor Fedorov, Yunyang Xiong, Ernie Chang, Yangyang Shi, Raghuraman Krishnamoorthi, Liangzhen Lai, Vikas Chandra:
MobileLLM: Optimizing Sub-billion Parameter Language Models for On-Device Use Cases. CoRR abs/2402.14905 (2024) - [i94]Jiawei Zhao, Zhenyu Zhang, Beidi Chen, Zhangyang Wang, Anima Anandkumar, Yuandong Tian:
GaLore: Memory-Efficient LLM Training by Gradient Low-Rank Projection. CoRR abs/2403.03507 (2024) - [i93]Hanshi Sun, Zhuoming Chen, Xinyu Yang, Yuandong Tian, Beidi Chen:
TriForce: Lossless Acceleration of Long Sequence Generation with Hierarchical Speculative Decoding. CoRR abs/2404.11912 (2024) - [i92]Morteza Behrooz, Yuandong Tian, William Ngan, Yael Yungster, Justin Wong, David Zax:
Holding the Line: A Study of Writers' Attitudes on Co-creativity with AI. CoRR abs/2404.13165 (2024) - [i91]Anselm Paulus, Arman Zharmagambetov, Chuan Guo, Brandon Amos, Yuandong Tian:
AdvPrompter: Fast Adaptive Adversarial Prompting for LLMs. CoRR abs/2404.16873 (2024) - [i90]Hanlin Zhu, Baihe Huang, Shaolun Zhang, Michael I. Jordan, Jiantao Jiao, Yuandong Tian, Stuart Russell:
Towards a Theoretical Understanding of the 'Reversal Curse' via Training Dynamics. CoRR abs/2405.04669 (2024) - [i89]Zechun Liu, Changsheng Zhao, Igor Fedorov, Bilge Soran, Dhruv Choudhary, Raghuraman Krishnamoorthi, Vikas Chandra, Yuandong Tian, Tijmen Blankevoort:
SpinQuant: LLM quantization with learned rotations. CoRR abs/2405.16406 (2024) - [i88]Ruisi Cai, Yuandong Tian, Zhangyang Wang, Beidi Chen:
LoCoCo: Dropping In Convolutions for Long Context Compression. CoRR abs/2406.05317 (2024) - [i87]Zhenyu Zhang, Ajay Jaiswal, Lu Yin, Shiwei Liu, Jiawei Zhao, Yuandong Tian, Zhangyang Wang:
Q-GaLore: Quantized GaLore with INT4 Projection and Layer-Adaptive Low-Rank Gradients. CoRR abs/2407.08296 (2024) - [i86]Ajay Jaiswal, Lu Yin, Zhenyu Zhang, Shiwei Liu, Jiawei Zhao, Yuandong Tian, Zhangyang Wang:
From GaLore to WeLore: How Low-Rank Weights Non-uniformly Emerge from Low-Rank Gradients. CoRR abs/2407.11239 (2024) - [i85]Tianhao Wu, Weizhe Yuan, Olga Golovneva, Jing Xu, Yuandong Tian, Jiantao Jiao, Jason Weston, Sainbayar Sukhbaatar:
Meta-Rewarding Language Models: Self-Improving Alignment with LLM-as-a-Meta-Judge. CoRR abs/2407.19594 (2024) - 2023
- [j9]Runlong Zhou, Zelin He, Yuandong Tian, Yi Wu, Simon Shaolei Du:
Understanding Curriculum Learning in Policy Optimization for Online Combinatorial Optimization. Trans. Mach. Learn. Res. 2023 (2023) - [c83]Kevin Yang, Dan Klein, Nanyun Peng, Yuandong Tian:
DOC: Improving Long Story Coherence With Detailed Outline Control. ACL (1) 2023: 3378-3465 - [c82]Taoan Huang
, Aaron M. Ferber, Yuandong Tian, Bistra Dilkina, Benoit Steiner:
Local Branching Relaxation Heuristics for Integer Linear Programs. CPAIOR 2023: 96-113 - [c81]Mulong Luo, Wenjie Xiong, Geunbae Lee, Yueying Li, Xiaomeng Yang, Amy Zhang, Yuandong Tian, Hsien-Hsin S. Lee, G. Edward Suh:
AutoCAT: Reinforcement Learning for Automated Exploration of Cache-Timing Attacks. HPCA 2023: 317-332 - [c80]Jiaxun Cui, Xiaomeng Yang, Mulong Luo, Geunbae Lee, Peter Stone, Hsien-Hsin S. Lee, Benjamin Lee, G. Edward Suh, Wenjie Xiong, Yuandong Tian:
MACTA: A Multi-agent Reinforcement Learning Approach for Cache Timing Attacks and Detection. ICLR 2023 - [c79]Zhengyao Jiang, Tianjun Zhang, Michael Janner, Yueying Li, Tim Rocktäschel, Edward Grefenstette, Yuandong Tian:
Efficient Planning in a Compact Latent Action Space. ICLR 2023 - [c78]Yuandong Tian:
Understanding the Role of Nonlinearity in Training Dynamics of Contrastive Learning. ICLR 2023 - [c77]Aaron M. Ferber, Taoan Huang, Daochen Zha, Martin Schubert, Benoit Steiner, Bistra Dilkina, Yuandong Tian:
SurCo: Learning Linear SURrogates for COmbinatorial Nonlinear Optimization Problems. ICML 2023: 10034-10052 - [c76]Taoan Huang, Aaron M. Ferber, Yuandong Tian, Bistra Dilkina, Benoit Steiner:
Searching Large Neighborhoods for Integer Linear Programs with Contrastive Learning. ICML 2023: 13869-13890 - [c75]Youwei Liang, Kevin Stone, Ali Shameli, Chris Cummins, Mostafa Elhoushi, Jiadong Guo, Benoit Steiner, Xiaomeng Yang, Pengtao Xie, Hugh James Leather, Yuandong Tian:
Learning Compiler Pass Orders using Coreset and Normalized Value Prediction. ICML 2023: 20746-20762 - [c74]Zichang Liu, Jue Wang, Tri Dao, Tianyi Zhou, Binhang Yuan, Zhao Song, Anshumali Shrivastava, Ce Zhang, Yuandong Tian, Christopher Ré, Beidi Chen:
Deja Vu: Contextual Sparsity for Efficient LLMs at Inference Time. ICML 2023: 22137-22176 - [c73]Daochen Zha, Louis Feng, Liang Luo, Bhargav Bhushanam, Zirui Liu, Yusuo Hu, Jade Nie, Yuzhen Huang, Yuandong Tian, Arun Kejariwal, Xia Hu:
Pre-train and Search: Efficient Embedding Table Sharding with Pre-trained Neural Cost Models. MLSys 2023 - [c72]Yuandong Tian, Yiping Wang, Beidi Chen, Simon S. Du:
Scan and Snap: Understanding Training Dynamics and Token Composition in 1-layer Transformer. NeurIPS 2023 - [c71]Zhenyu Zhang, Ying Sheng, Tianyi Zhou, Tianlong Chen, Lianmin Zheng, Ruisi Cai, Zhao Song, Yuandong Tian, Christopher Ré, Clark W. Barrett, Zhangyang Wang, Beidi Chen:
H2O: Heavy-Hitter Oracle for Efficient Generative Inference of Large Language Models. NeurIPS 2023 - [c70]Arman Zharmagambetov, Brandon Amos, Aaron M. Ferber, Taoan Huang, Bistra Dilkina, Yuandong Tian:
Landscape Surrogate: Learning Decision Losses for Mathematical Optimization Under Partial Information. NeurIPS 2023 - [c69]Weilin Cong, Yanhong Wu, Yuandong Tian, Mengting Gu, Yinglong Xia, Chun-cheng Jason Chen, Mehrdad Mahdavi:
DyFormer : A Scalable Dynamic Graph Transformer with Provable Benefits on Generalization Ability. SDM 2023: 442-450 - [c68]Yihao Zhao, Xiaoxiang Zhang, Hang Zhu, Ying Zhang, Zhaodong Wang, Yuandong Tian, Alex Nikulkov, Joao Ferreira, Xuanzhe Liu, Xin Jin:
Klotski: Efficient and Safe Network Migration of Large Production Datacenters. SIGCOMM 2023: 783-797 - [i84]Andrew Cohen, Weiping Dou, Jiang Zhu, Slawomir Koziel, Peter Renner, Jan-Ove Mattsson, Xiaomeng Yang, Beidi Chen, Kevin Stone, Yuandong Tian:
Modeling Scattering Coefficients using Self-Attentive Complex Polynomials with Image-based Representation. CoRR abs/2301.02747 (2023) - [i83]Youwei Liang, Kevin Stone, Ali Shameli, Chris Cummins, Mostafa Elhoushi, Jiadong Guo, Benoit Steiner, Xiaomeng Yang, Pengtao Xie, Hugh Leather, Yuandong Tian:
Learning Compiler Pass Orders using Coreset and Normalized Value Prediction. CoRR abs/2301.05104 (2023) - [i82]Taoan Huang, Aaron M. Ferber, Yuandong Tian, Bistra Dilkina, Benoit Steiner:
Searching Large Neighborhoods for Integer Linear Programs with Contrastive Learning. CoRR abs/2302.01578 (2023) - [i81]Randall Balestriero, Mark Ibrahim, Vlad Sobal, Ari Morcos, Shashank Shekhar, Tom Goldstein, Florian Bordes, Adrien Bardes, Grégoire Mialon, Yuandong Tian, Avi Schwarzschild, Andrew Gordon Wilson, Jonas Geiping, Quentin Garrido, Pierre Fernandez, Amir Bar, Hamed Pirsiavash, Yann LeCun, Micah Goldblum:
A Cookbook of Self-Supervised Learning. CoRR abs/2304.12210 (2023) - [i80]Daochen Zha, Louis Feng, Liang Luo, Bhargav Bhushanam, Zirui Liu, Yusuo Hu, Jade Nie, Yuzhen Huang, Yuandong Tian, Arun Kejariwal, Xia Hu:
Pre-train and Search: Efficient Embedding Table Sharding with Pre-trained Neural Cost Models. CoRR abs/2305.01868 (2023) - [i79]Yuandong Tian, Yiping Wang, Beidi Chen, Simon S. Du:
Scan and Snap: Understanding Training Dynamics and Token Composition in 1-layer Transformer. CoRR abs/2305.16380 (2023) - [i78]Zhenyu Zhang, Ying Sheng, Tianyi Zhou, Tianlong Chen, Lianmin Zheng, Ruisi Cai, Zhao Song, Yuandong Tian, Christopher Ré, Clark W. Barrett, Zhangyang Wang, Beidi Chen:
H2O: Heavy-Hitter Oracle for Efficient Generative Inference of Large Language Models. CoRR abs/2306.14048 (2023) - [i77]Shouyuan Chen, Sherman Wong, Liangjian Chen, Yuandong Tian:
Extending Context Window of Large Language Models via Positional Interpolation. CoRR abs/2306.15595 (2023) - [i76]Arman Zharmagambetov, Brandon Amos, Aaron M. Ferber, Taoan Huang, Bistra Dilkina, Yuandong Tian:
Landscape Surrogate: Learning Decision Losses for Mathematical Optimization Under Partial Information. CoRR abs/2307.08964 (2023) - [i75]Kevin Yang, Dan Klein, Asli Celikyilmaz, Nanyun Peng, Yuandong Tian:
RLCD: Reinforcement Learning from Contrast Distillation for Language Model Alignment. CoRR abs/2307.12950 (2023) - [i74]Guangxuan Xiao, Yuandong Tian, Beidi Chen, Song Han, Mike Lewis:
Efficient Streaming Language Models with Attention Sinks. CoRR abs/2309.17453 (2023) - [i73]Yuandong Tian, Yiping Wang, Zhenyu Zhang, Beidi Chen, Simon S. Du:
JoMA: Demystifying Multilayer Transformers via JOint Dynamics of MLP and Attention. CoRR abs/2310.00535 (2023) - [i72]Aaron M. Ferber, Arman Zharmagambetov, Taoan Huang, Bistra Dilkina, Yuandong Tian:
GenCO: Generating Diverse Solutions to Design Problems with Combinatorial Nature. CoRR abs/2310.02442 (2023) - [i71]Danqing Wang, Kevin Yang, Hanlin Zhu, Xiaomeng Yang, Andrew Cohen, Lei Li, Yuandong Tian:
Learning Personalized Story Evaluation. CoRR abs/2310.03304 (2023) - [i70]Hanlin Zhu, Andrew Cohen, Danqing Wang, Kevin Yang, Xiaomeng Yang, Jiantao Jiao, Yuandong Tian:
End-to-end Story Plot Generator. CoRR abs/2310.08796 (2023) - [i69]Zichang Liu, Jue Wang, Tri Dao, Tianyi Zhou, Binhang Yuan, Zhao Song, Anshumali Shrivastava, Ce Zhang, Yuandong Tian, Christopher Ré, Beidi Chen:
Deja Vu: Contextual Sparsity for Efficient LLMs at Inference Time. CoRR abs/2310.17157 (2023) - [i68]Zhengyao Jiang, Yingchen Xu, Nolan Wagener, Yicheng Luo, Michael Janner, Edward Grefenstette, Tim Rocktäschel, Yuandong Tian:
H-GAP: Humanoid Control with a Generalist Planner. CoRR abs/2312.02682 (2023) - 2022
- [j8]Linnan Wang, Saining Xie, Teng Li, Rodrigo Fonseca, Yuandong Tian:
Sample-Efficient Neural Architecture Search by Learning Actions for Monte Carlo Tree Search. IEEE Trans. Pattern Anal. Mach. Intell. 44(9): 5503-5515 (2022) - [c67]Cheng Fu, Hanxian Huang, Bram Wasti, Chris Cummins, Riyadh Baghdadi, Kim M. Hazelwood, Yuandong Tian, Jishen Zhao, Hugh Leather:
Q-gym: An Equality Saturation Framework for DNN Inference Exploiting Weight Repetition. PACT 2022: 291-303 - [c66]Hui Shi, Sicun Gao, Yuandong Tian, Xinyun Chen, Jishen Zhao:
Learning Bounded Context-Free-Grammar via LSTM and the Transformer: Difference and the Explanations. AAAI 2022: 8267-8276 - [c65]Yulai Zhao, Yuandong Tian, Jason D. Lee, Simon S. Du:
Provably Efficient Policy Optimization for Two-Player Zero-Sum Markov Games. AISTATS 2022: 2736-2761 - [c64]Chris Cummins, Bram Wasti, Jiadong Guo, Brandon Cui, Jason Ansel, Sahir Gomez, Somya Jain, Jia Liu, Olivier Teytaud, Benoit Steiner, Yuandong Tian, Hugh Leather:
CompilerGym: Robust, Performant Compiler Optimization Environments for AI Research. CGO 2022: 92-105 - [c63]Xiao Wang, Haoqi Fan, Yuandong Tian, Daisuke Kihara, Xinlei Chen:
On the Importance of Asymmetry for Siamese Representation Learning. CVPR 2022: 16549-16558 - [c62]Kevin Yang, Yuandong Tian, Nanyun Peng, Dan Klein:
Re3: Generating Longer Stories With Recursive Reprompting and Revision. EMNLP 2022: 4393-4479 - [c61]Chengyue Gong, Dilin Wang, Meng Li, Xinlei Chen, Zhicheng Yan, Yuandong Tian, Qiang Liu, Vikas Chandra:
NASViT: Neural Architecture Search for Efficient Vision Transformers with Gradient Conflict aware Supernet Training. ICLR 2022 - [c60]Li Jing, Pascal Vincent, Yann LeCun, Yuandong Tian:
Understanding Dimensional Collapse in Contrastive Self-supervised Learning. ICLR 2022 - [c59]Yiyang Zhao, Linnan Wang, Kevin Yang, Tianjun Zhang, Tian Guo, Yuandong Tian:
Multi-objective Optimization by Learning Space Partition. ICLR 2022 - [c58]Tongzhou Wang, Simon S. Du, Antonio Torralba, Phillip Isola, Amy Zhang, Yuandong Tian:
Denoised MDPs: Learning World Models Better Than the World Itself. ICML 2022: 22591-22612 - [c57]Daochen Zha, Louis Feng, Bhargav Bhushanam, Dhruv Choudhary, Jade Nie, Yuandong Tian, Jay Chae, Yinbin Ma, Arun Kejariwal, Xia Hu:
AutoShard: Automated Embedding Table Sharding for Recommender Systems. KDD 2022: 4461-4471 - [c56]Yuandong Tian:
Understanding Deep Contrastive Learning via Coordinate-wise Optimization. NeurIPS 2022 - [c55]Daochen Zha, Louis Feng, Qiaoyu Tan, Zirui Liu, Kwei-Herng Lai, Bhargav Bhushanam, Yuandong Tian, Arun Kejariwal, Xia Hu:
DreamShard: Generalizable Embedding Table Placement for Recommender Systems. NeurIPS 2022 - [i67]Yuandong Tian:
Deep Contrastive Learning is Provably (almost) Principal Component Analysis. CoRR abs/2201.12680 (2022) - [i66]Runlong Zhou, Yuandong Tian, Yi Wu, Simon S. Du:
Understanding Curriculum Learning in Policy Optimization for Solving Combinatorial Optimization Problems. CoRR abs/2202.05423 (2022) - [i65]Xiao Wang, Haoqi Fan, Yuandong Tian, Daisuke Kihara, Xinlei Chen:
On the Importance of Asymmetry for Siamese Representation Learning. CoRR abs/2204.00613 (2022) - [i64]Yuandong Tian:
Understanding the Role of Nonlinearity in Training Dynamics of Contrastive Learning. CoRR abs/2206.01342 (2022) - [i63]Tongzhou Wang, Simon S. Du, Antonio Torralba, Phillip Isola, Amy Zhang, Yuandong Tian:
Denoised MDPs: Learning World Models Better Than the World Itself. CoRR abs/2206.15477 (2022) - [i62]Daochen Zha, Louis Feng, Bhargav Bhushanam, Dhruv Choudhary, Jade Nie, Yuandong Tian, Jay Chae, Yinbin Ma, Arun Kejariwal, Xia Hu:
AutoShard: Automated Embedding Table Sharding for Recommender Systems. CoRR abs/2208.06399 (2022) - [i61]Mulong Luo, Wenjie Xiong, Geunbae Lee, Yueying Li, Xiaomeng Yang, Amy Zhang, Yuandong Tian, Hsien-Hsin S. Lee, G. Edward Suh:
AutoCAT: Reinforcement Learning for Automated Exploration of Cache Timing-Channel Attacks. CoRR abs/2208.08025 (2022) - [i60]Zhengyao Jiang, Tianjun Zhang, Michael Janner, Yueying Li, Tim Rocktäschel, Edward Grefenstette, Yuandong Tian:
Efficient Planning in a Compact Latent Action Space. CoRR abs/2208.10291 (2022) - [i59]Daochen Zha, Louis Feng, Qiaoyu Tan, Zirui Liu, Kwei-Herng Lai, Bhargav Bhushanam, Yuandong Tian, Arun Kejariwal, Xia Hu:
DreamShard: Generalizable Embedding Table Placement for Recommender Systems. CoRR abs/2210.02023 (2022) - [i58]Kevin Yang, Yuandong Tian, Nanyun Peng, Dan Klein:
Re3: Generating Longer Stories With Recursive Reprompting and Revision. CoRR abs/2210.06774 (2022) - [i57]Aaron M. Ferber, Taoan Huang, Daochen Zha, Martin Schubert, Benoit Steiner, Bistra Dilkina, Yuandong Tian:
SurCo: Learning Linear Surrogates For Combinatorial Nonlinear Optimization Problems. CoRR abs/2210.12547 (2022) - [i56]Minghao Xu, Yuanfan Guo, Yi Xu, Jian Tang, Xinlei Chen, Yuandong Tian:
EurNet: Efficient Multi-Range Relational Modeling of Spatial Multi-Relational Data. CoRR abs/2211.12941 (2022) - [i55]Taoan Huang, Aaron M. Ferber, Yuandong Tian, Bistra Dilkina, Benoit Steiner:
Local Branching Relaxation Heuristics for Integer Linear Programs. CoRR abs/2212.08183 (2022) - [i54]Kevin Yang, Dan Klein, Nanyun Peng, Yuandong Tian:
DOC: Improving Long Story Coherence With Detailed Outline Control. CoRR abs/2212.10077 (2022) - 2021
- [j7]Tianyu Li, Roberto Calandra, Deepak Pathak, Yuandong Tian, Franziska Meier, Akshara Rai:
Planning in Learned Latent Action Spaces for Generalizable Legged Locomotion. IEEE Robotics Autom. Lett. 6(2): 2682-2689 (2021) - [c54]Zhuolin Yang, Zhaoxi Chen, Tiffany Cai, Xinyun Chen, Bo Li, Yuandong Tian:
Understanding Robustness in Teacher-Student Setting: A New Perspective. AISTATS 2021: 3313-3321 - [c53]Zhicheng Yan, Xiaoliang Dai, Peizhao Zhang, Yuandong Tian, Bichen Wu, Matt Feiszli:
FP-NAS: Fast Probabilistic Neural Architecture Search. CVPR 2021: 15139-15148 - [c52]Xiaoliang Dai, Alvin Wan, Peizhao Zhang, Bichen Wu, Zijian He, Zhen Wei, Kan Chen, Yuandong Tian, Matthew Yu, Peter Vajda, Joseph E. Gonzalez:
FBNetV3: Joint Architecture-Recipe Search Using Predictor Pretraining. CVPR 2021: 16276-16285 - [c51]Cheng Fu, Hanxian Huang, Xinyun Chen, Yuandong Tian, Jishen Zhao:
Learn-to-Share: A Hardware-friendly Transfer Learning Framework Exploiting Computation and Parameter Sharing. ICML 2021: 3469-3479 - [c50]Yuandong Tian, Xinlei Chen, Surya Ganguli:
Understanding self-supervised learning dynamics without contrastive pairs. ICML 2021: 10268-10278 - [c49]Yiyang Zhao, Linnan Wang, Yuandong Tian, Rodrigo Fonseca, Tian Guo:
Few-Shot Neural Architecture Search. ICML 2021: 12707-12718 - [c48]Kevin Yang, Tianjun Zhang, Chris Cummins, Brandon Cui, Benoit Steiner, Linnan Wang, Joseph E. Gonzalez, Dan Klein, Yuandong Tian:
Learning Space Partitions for Path Planning. NeurIPS 2021: 378-391 - [c47]Tianjun Zhang, Paria Rashidinejad, Jiantao Jiao, Yuandong Tian, Joseph E. Gonzalez, Stuart Russell:
MADE: Exploration via Maximizing Deviation from Explored Regions. NeurIPS 2021: 9663-9680 - [c46]Xinyun Chen, Dawn Song, Yuandong Tian:
Latent Execution for Neural Program Synthesis Beyond Domain-Specific Languages. NeurIPS 2021: 22196-22208 - [c45]Tianjun Zhang, Huazhe Xu, Xiaolong Wang, Yi Wu, Kurt Keutzer, Joseph E. Gonzalez, Yuandong Tian:
NovelD: A Simple yet Effective Exploration Criterion. NeurIPS 2021: 25217-25230 - [c44]Hang Zhu, Varun Gupta, Satyajeet Singh Ahuja, Yuandong Tian, Ying Zhang, Xin Jin:
Network planning with deep reinforcement learning. SIGCOMM 2021: 258-271 - [i53]Yuandong Tian, Xinlei Chen, Surya Ganguli:
Understanding self-supervised Learning Dynamics without Contrastive Pairs. CoRR abs/2102.06810 (2021) - [i52]Yulai Zhao, Yuandong Tian, Jason D. Lee, Simon S. Du:
Provably Efficient Policy Gradient Methods for Two-Player Zero-Sum Markov Games. CoRR abs/2102.08903 (2021) - [i51]Zhuolin Yang, Zhaoxi Chen, Tiffany Cai, Xinyun Chen, Bo Li, Yuandong Tian:
Understanding Robustness in Teacher-Student Setting: A New Perspective. CoRR abs/2102.13170 (2021) - [i50]Tianjun Zhang, Paria Rashidinejad, Jiantao Jiao, Yuandong Tian, Joseph Gonzalez, Stuart Russell:
MADE: Exploration via Maximizing Deviation from Explored Regions. CoRR abs/2106.10268 (2021) - [i49]Kevin Yang, Tianjun Zhang, Chris Cummins, Brandon Cui, Benoit Steiner, Linnan Wang, Joseph E. Gonzalez, Dan Klein, Yuandong Tian:
Learning Space Partitions for Path Planning. CoRR abs/2106.10544 (2021) - [i48]Xinyun Chen, Dawn Song, Yuandong Tian:
Latent Execution for Neural Program Synthesis Beyond Domain-Specific Languages. CoRR abs/2107.00101 (2021) - [i47]Chris Cummins, Bram Wasti, Jiadong Guo, Brandon Cui, Jason Ansel, Sahir Gomez, Somya Jain, Jia Liu, Olivier Teytaud, Benoit Steiner, Yuandong Tian, Hugh Leather:
CompilerGym: Robust, Performant Compiler Optimization Environments for AI Research. CoRR abs/2109.08267 (2021) - [i46]Yiyang Zhao, Linnan Wang, Kevin Yang, Tianjun Zhang, Tian Guo, Yuandong Tian:
Multi-objective Optimization by Learning Space Partitions. CoRR abs/2110.03173 (2021) - [i45]Xiang Wang, Xinlei Chen, Simon S. Du, Yuandong Tian:
Towards Demystifying Representation Learning with Non-contrastive Self-supervision. CoRR abs/2110.04947 (2021) - [i44]Li Jing, Pascal Vincent, Yann LeCun, Yuandong Tian:
Understanding Dimensional Collapse in Contrastive Self-supervised Learning. CoRR abs/2110.09348 (2021) - [i43]Weilin Cong, Yanhong Wu, Yuandong Tian, Mengting Gu, Yinglong Xia, Mehrdad Mahdavi, Chun-cheng Jason Chen:
Dynamic Graph Representation Learning via Graph Transformer Networks. CoRR abs/2111.10447 (2021) - [i42]Hui Shi, Sicun Gao, Yuandong Tian, Xinyun Chen, Jishen Zhao:
Learning Bounded Context-Free-Grammar via LSTM and the Transformer: Difference and Explanations. CoRR abs/2112.09174 (2021) - 2020
- [j6]