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ORCIDYuandong Tian
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- affiliation: Carnegie Mellon University
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2020 – today
- 2024
[c94]Danqing Wang, Kevin Yang, Hanlin Zhu, Xiaomeng Yang, Andrew Cohen, Lei Li, Yuandong Tian:
Learning Personalized Alignment for Evaluating Open-ended Text Generation. EMNLP 2024: 13274-13292- [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 - [i102]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) - [i101]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) - [i100]Zihan Ding, Amy Zhang, Yuandong Tian, Qinqing Zheng:
Diffusion World Model. CoRR abs/2402.03570 (2024) - [i99]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) - [i98]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) - [i97]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) - [i96]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) - [i95]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) - [i94]Anselm Paulus, Arman Zharmagambetov, Chuan Guo, Brandon Amos, Yuandong Tian:
AdvPrompter: Fast Adaptive Adversarial Prompting for LLMs. CoRR abs/2404.16873 (2024) - [i93]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) - [i92]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) - [i91]Ruisi Cai, Yuandong Tian, Zhangyang Wang, Beidi Chen:
LoCoCo: Dropping In Convolutions for Long Context Compression. CoRR abs/2406.05317 (2024) - [i90]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) - [i89]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) - [i88]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) - [i87]Yun Joon Soh, Hanxian Huang, Yuandong Tian, Jishen Zhao:
You Only Use Reactive Attention Slice For Long Context Retrieval. CoRR abs/2409.13695 (2024) - [i86]Tengyu Xu, Eryk Helenowski, Karthik Abinav Sankararaman, Di Jin, Kaiyan Peng, Eric Han, Shaoliang Nie, Chen Zhu, Hejia Zhang, Wenxuan Zhou, Zhouhao Zeng, Yun He, Karishma Mandyam, Arya Talabzadeh, Madian Khabsa, Gabriel Cohen, Yuandong Tian, Hao Ma, Sinong Wang, Han Fang:
The Perfect Blend: Redefining RLHF with Mixture of Judges. CoRR abs/2409.20370 (2024) - [i85]Yuandong Tian:
Composing Global Optimizers to Reasoning Tasks via Algebraic Objects in Neural Nets. CoRR abs/2410.01779 (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]Cheng Fu, Huili Chen, Zhenheng Yang, Farinaz Koushanfar, Yuandong Tian, Jishen Zhao:
Enhancing Model Parallelism in Neural Architecture Search for Multidevice System. IEEE Micro 40(5): 46-55 (2020) - [c43]Linnan Wang, Yiyang Zhao, Yuu Jinnai, Yuandong Tian, Rodrigo Fonseca:
Neural Architecture Search Using Deep Neural Networks and Monte Carlo Tree Search. AAAI 2020: 9983-9991 - [c42]Alvin Wan, Xiaoliang Dai, Peizhao Zhang, Zijian He, Yuandong Tian, Saining Xie, Bichen Wu, Matthew Yu, Tao Xu, Kan Chen, Peter Vajda, Joseph E. Gonzalez:
FBNetV2: Differentiable Neural Architecture Search for Spatial and Channel Dimensions. CVPR 2020: 12962-12971 - [c41]Hui Shi, Yang Zhang, Xinyun Chen, Yuandong Tian, Jishen Zhao:
Deep Symbolic Superoptimization Without Human Knowledge. ICLR 2020 - [c40]Haonan Yu, Sergey Edunov, Yuandong Tian, Ari S. Morcos:
Playing the lottery with rewards and multiple languages: lottery tickets in RL and NLP. ICLR 2020 - [c39]Yuandong Tian:
Student Specialization in Deep Rectified Networks With Finite Width and Input Dimension. ICML 2020: 9470-9480 - [c38]Qingquan Song, Dehua Cheng, Hanning Zhou, Jiyan Yang, Yuandong Tian, Xia Hu:
Towards Automated Neural Interaction Discovery for Click-Through Rate Prediction. KDD 2020: 945-955 - [c37]Yuandong Tian, Qucheng Gong, Yu Jiang:
Joint Policy Search for Multi-agent Collaboration with Imperfect Information. NeurIPS 2020 - [c36]Linnan Wang, Rodrigo Fonseca, Yuandong Tian:
Learning Search Space Partition for Black-box Optimization using Monte Carlo Tree Search. NeurIPS 2020 - [i41]Alvin Wan, Xiaoliang Dai, Peizhao Zhang, Zijian He, Yuandong Tian, Saining Xie, Bichen Wu, Matthew Yu, Tao Xu, Kan Chen, Peter Vajda, Joseph E. Gonzalez:
FBNetV2: Differentiable Neural Architecture Search for Spatial and Channel Dimensions. CoRR abs/2004.05565 (2020) - [i40]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 Neural Acquisition Function. CoRR abs/2006.02049 (2020) - [i39]Yiyang Zhao, Linnan Wang, Yuandong Tian, Rodrigo Fonseca, Tian Guo:
Few-shot Neural Architecture Search. CoRR abs/2006.06863 (2020) - [i38]Linnan Wang, Rodrigo Fonseca, Yuandong Tian:
Learning Search Space Partition for Black-box Optimization using Monte Carlo Tree Search. CoRR abs/2007.00708 (2020) - [i37]Qingquan Song, Dehua Cheng, Hanning Zhou, Jiyan Yang, Yuandong Tian, Xia Hu:
Towards Automated Neural Interaction Discovery for Click-Through Rate Prediction. CoRR abs/2007.06434 (2020) - [i36]Yuandong Tian, Qucheng Gong, Tina Jiang:
Joint Policy Search for Multi-agent Collaboration with Imperfect Information. CoRR abs/2008.06495 (2020) - [i35]Tianyu Li, Roberto Calandra, Deepak Pathak, Yuandong Tian, Franziska Meier, Akshara Rai:
Planning in Learned Latent Action Spaces for Generalizable Legged Locomotion. CoRR abs/2008.11867 (2020) - [i34]Hongzi Mao, Shannon Chen, Drew Dimmery, Shaun Singh, Drew Blaisdell, Yuandong Tian, Mohammad Alizadeh, Eytan Bakshy:
Real-world Video Adaptation with Reinforcement Learning. CoRR abs/2008.12858 (2020) - [i33]Yuandong Tian, Lantao Yu, Xinlei Chen, Surya Ganguli:
Understanding Self-supervised Learning with Dual Deep Networks. CoRR abs/2010.00578 (2020) - [i32]Tianjun Zhang, Huazhe Xu, Xiaolong Wang, Yi Wu, Kurt Keutzer, Joseph E. Gonzalez, Yuandong Tian:
Multi-Agent Collaboration via Reward Attribution Decomposition. CoRR abs/2010.08531 (2020) - [i31]Zhicheng Yan, Xiaoliang Dai, Peizhao Zhang, Yuandong Tian, Bichen Wu, Matt Feiszli:
FP-NAS: Fast Probabilistic Neural Architecture Search. CoRR abs/2011.10949 (2020) - [i30]Tianjun Zhang, Huazhe Xu, Xiaolong Wang, Yi Wu, Kurt Keutzer, Joseph E. Gonzalez, Yuandong Tian:
BeBold: Exploration Beyond the Boundary of Explored Regions. CoRR abs/2012.08621 (2020)
2010 – 2019
- 2019
- [c35]Jin-Hwa Kim, Nikita Kitaev, Xinlei Chen, Marcus Rohrbach, Byoung-Tak Zhang, Yuandong Tian, Dhruv Batra, Devi Parikh:
CoDraw: Collaborative Drawing as a Testbed for Grounded Goal-driven Communication. ACL (1) 2019: 6495-6513 - [c34]Bichen Wu, Xiaoliang Dai, Peizhao Zhang, Yanghan Wang, Fei Sun, Yiming Wu, Yuandong Tian, Peter Vajda, Yangqing Jia, Kurt Keutzer:
FBNet: Hardware-Aware Efficient ConvNet Design via Differentiable Neural Architecture Search. CVPR 2019: 10734-10742 - [c33]Yi Wu, Yuxin Wu, Aviv Tamar, Stuart Russell, Georgia Gkioxari, Yuandong Tian:
Bayesian Relational Memory for Semantic Visual Navigation. ICCV 2019: 2769-2779 - [c32]Yuping Luo, Huazhe Xu, Yuanzhi Li, Yuandong Tian, Trevor Darrell, Tengyu Ma:
Algorithmic Framework for Model-based Deep Reinforcement Learning with Theoretical Guarantees. ICLR (Poster) 2019 - [c31]Tianmin Shu, Yuandong Tian:
M^3RL: Mind-aware Multi-agent Management Reinforcement Learning. ICLR (Poster) 2019 - [c30]Yuandong Tian, Jerry Ma, Qucheng Gong, Shubho Sengupta, Zhuoyuan Chen, James Pinkerton, Larry Zitnick:
ELF OpenGo: an analysis and open reimplementation of AlphaZero. ICML 2019: 6244-6253 - [c29]Cheng Fu, Huili Chen, Haolan Liu, Xinyun Chen, Yuandong Tian, Farinaz Koushanfar, Jishen Zhao:
Coda: An End-to-End Neural Program Decompiler. NeurIPS 2019: 3703-3714 - [c28]Ari S. Morcos, Haonan Yu, Michela Paganini, Yuandong Tian:
One ticket to win them all: generalizing lottery ticket initializations across datasets and optimizers. NeurIPS 2019: 4933-4943 - [c27]Xinyun Chen, Yuandong Tian:
Learning to Perform Local Rewriting for Combinatorial Optimization. NeurIPS 2019: 6278-6289 - [c26]Hengyuan Hu, Denis Yarats, Qucheng Gong, Yuandong Tian, Mike Lewis:
Hierarchical Decision Making by Generating and Following Natural Language Instructions. NeurIPS 2019: 10025-10034 - [i29]Yuandong Tian, Jerry Ma, Qucheng Gong, Shubho Sengupta, Zhuoyuan Chen, James Pinkerton, C. Lawrence Zitnick:
ELF OpenGo: An Analysis and Open Reimplementation of AlphaZero. CoRR abs/1902.04522 (2019) - [i28]Linnan Wang, Yiyang Zhao, Yuu Jinnai, Yuandong Tian, Rodrigo Fonseca:
AlphaX: eXploring Neural Architectures with Deep Neural Networks and Monte Carlo Tree Search. CoRR abs/1903.11059 (2019) - [i27]Yuandong Tian, Tina Jiang, Qucheng Gong, Ari S. Morcos:
Luck Matters: Understanding Training Dynamics of Deep ReLU Networks. CoRR abs/1905.13405 (2019) - [i26]Hengyuan Hu, Denis Yarats, Qucheng Gong, Yuandong Tian, Mike Lewis:
Hierarchical Decision Making by Generating and Following Natural Language Instructions. CoRR abs/1906.00744 (2019) - [i25]Haonan Yu, Sergey Edunov, Yuandong Tian, Ari S. Morcos:
Playing the lottery with rewards and multiple languages: lottery tickets in RL and NLP. CoRR abs/1906.02768 (2019) - [i24]Ari S. Morcos, Haonan Yu, Michela Paganini, Yuandong Tian:
One ticket to win them all: generalizing lottery ticket initializations across datasets and optimizers. CoRR abs/1906.02773 (2019) - [i23]Linnan Wang, Saining Xie, Teng Li, Rodrigo Fonseca, Yuandong Tian:
Sample-Efficient Neural Architecture Search by Learning Action Space. CoRR abs/1906.06832 (2019) - [i22]Cheng Fu, Huili Chen, Haolan Liu, Xinyun Chen, Yuandong Tian, Farinaz Koushanfar, Jishen Zhao:
A Neural-based Program Decompiler. CoRR abs/1906.12029 (2019) - [i21]Yi Wu, Yuxin Wu, Aviv Tamar, Stuart Russell, Georgia Gkioxari, Yuandong Tian:
Bayesian Relational Memory for Semantic Visual Navigation. CoRR abs/1909.04306 (2019) - [i20]Yuandong Tian:
Over-parameterization as a Catalyst for Better Generalization of Deep ReLU network. CoRR abs/1909.13458 (2019) - 2018
- [j5]Jiajun Wu, Tianfan Xue, Joseph J. Lim, Yuandong Tian, Joshua B. Tenenbaum, Antonio Torralba, William T. Freeman:
3D Interpreter Networks for Viewer-Centered Wireframe Modeling. Int. J. Comput. Vis. 126(9): 1009-1026 (2018) - [j4]I-Chen Wu, Chang-Shing Lee, Yuandong Tian, Martin Müller:
Guest Editorial Special Issue on Deep/Reinforcement Learning and Games. IEEE Trans. Games 10(4): 333-335 (2018) - [c25]Simon S. Du, Jason D. Lee, Yuandong Tian:
When is a Convolutional Filter Easy to Learn? ICLR (Poster) 2018 - [c24]Yi Wu, Yuxin Wu, Georgia Gkioxari, Yuandong Tian:
Building Generalizable Agents with a Realistic and Rich 3D Environment. ICLR (Workshop) 2018 - [c23]Simon S. Du, Jason D. Lee, Yuandong Tian, Aarti Singh, Barnabás Póczos:
Gradient Descent Learns One-hidden-layer CNN: Don't be Afraid of Spurious Local Minima. ICML 2018: 1338-1347 - [c22]Wenling Shang, Kihyuk Sohn, Yuandong Tian:
Channel-Recurrent Autoencoding for Image Modeling. WACV 2018: 1195-1204 - [i19]Yi Wu, Yuxin Wu, Georgia Gkioxari, Yuandong Tian:
Building Generalizable Agents with a Realistic and Rich 3D Environment. CoRR abs/1801.02209 (2018) - [i18]Jiajun Wu, Tianfan Xue, Joseph J. Lim, Yuandong Tian, Joshua B. Tenenbaum, Antonio Torralba, William T. Freeman:
3D Interpreter Networks for Viewer-Centered Wireframe Modeling. CoRR abs/1804.00782 (2018) - [i17]Huazhe Xu, Yuanzhi Li, Yuandong Tian, Trevor Darrell, Tengyu Ma:
Algorithmic Framework for Model-based Reinforcement Learning with Theoretical Guarantees. CoRR abs/1807.03858 (2018) - [i16]Yuandong Tian:
A theoretical framework for deep locally connected ReLU network. CoRR abs/1809.10829 (2018) - [i15]Yi Wu, Yuxin Wu, Aviv Tamar, Stuart Russell, Georgia Gkioxari, Yuandong Tian:
Learning and Planning with a Semantic Model. CoRR abs/1809.10842 (2018) - [i14]Tianmin Shu, Yuandong Tian:
M^3RL: Mind-aware Multi-agent Management Reinforcement Learning. CoRR abs/1810.00147 (2018) - [i13]Xinyun Chen, Yuandong Tian:
Learning to Progressively Plan. CoRR abs/1810.00337 (2018) - [i12]Bichen Wu, Yanghan Wang, Peizhao Zhang, Yuandong Tian, Peter Vajda, Kurt Keutzer:
Mixed Precision Quantization of ConvNets via Differentiable Neural Architecture Search. CoRR abs/1812.00090 (2018) - [i11]Bichen Wu, Xiaoliang Dai, Peizhao Zhang, Yanghan Wang, Fei Sun, Yiming Wu, Yuandong Tian, Peter Vajda, Yangqing Jia, Kurt Keutzer:
FBNet: Hardware-Aware Efficient ConvNet Design via Differentiable Neural Architecture Search. CoRR abs/1812.03443 (2018) - 2017
- [c21]Yan Zhu, Yuandong Tian, Dimitris N. Metaxas, Piotr Dollár:
Semantic Amodal Segmentation. CVPR 2017: 3001-3009 - [c20]Yuandong Tian:
Symmetry-Breaking Convergence Analysis of Certain Two-layered Neural Networks with ReLU nonlinearity. ICLR (Workshop) 2017 - [c19]Yuxin Wu, Yuandong Tian:
Training Agent for First-Person Shooter Game with Actor-Critic Curriculum Learning. ICLR (Poster) 2017 - [c18]Yuandong Tian:
An Analytical Formula of Population Gradient for two-layered ReLU network and its Applications in Convergence and Critical Point Analysis. ICML 2017: 3404-3413 - [c17]Yuandong Tian, Qucheng Gong, Wenling Shang, Yuxin Wu, C. Lawrence Zitnick:
ELF: An Extensive, Lightweight and Flexible Research Platform for Real-time Strategy Games. NIPS 2017: 2659-2669 - [i10]Yuandong Tian:
An Analytical Formula of Population Gradient for two-layered ReLU network and its Applications in Convergence and Critical Point Analysis. CoRR abs/1703.00560 (2017) - [i9]Wenling Shang, Kihyuk Sohn, Zeynep Akata, Yuandong Tian:
Channel-Recurrent Variational Autoencoders. CoRR abs/1706.03729 (2017) - [i8]Yuandong Tian, Qucheng Gong, Wenling Shang, Yuxin Wu, Larry Zitnick:
ELF: An Extensive, Lightweight and Flexible Research Platform for Real-time Strategy Games. CoRR abs/1707.01067 (2017) - [i7]Simon S. Du, Jason D. Lee, Yuandong Tian:
When is a Convolutional Filter Easy To Learn? CoRR abs/1709.06129 (2017) - [i6]Simon S. Du, Jason D. Lee, Yuandong Tian, Barnabás Póczos, Aarti Singh:
Gradient Descent Learns One-hidden-layer CNN: Don't be Afraid of Spurious Local Minima. CoRR abs/1712.00779 (2017) - [i5]Jin-Hwa Kim, Devi Parikh, Dhruv Batra, Byoung-Tak Zhang, Yuandong Tian:
CoDraw: Visual Dialog for Collaborative Drawing. CoRR abs/1712.05558 (2017) - 2016
- [c16]Jiajun Wu, Tianfan Xue, Joseph J. Lim, Yuandong Tian, Joshua B. Tenenbaum, Antonio Torralba, William T. Freeman:
Single Image 3D Interpreter Network. ECCV (6) 2016: 365-382 - [c15]Yuandong Tian, Yan Zhu:
Better Computer Go Player with Neural Network and Long-term Prediction. ICLR (Poster) 2016 - [i4]Jiajun Wu, Tianfan Xue, Joseph J. Lim, Yuandong Tian, Joshua B. Tenenbaum, Antonio Torralba, William T. Freeman:
Single Image 3D Interpreter Network. CoRR abs/1604.08685 (2016) - 2015
- [j3]Yuandong Tian, Srinivasa G. Narasimhan:
Theory and Practice of Hierarchical Data-driven Descent for Optimal Deformation Estimation. Int. J. Comput. Vis. 115(1): 44-67 (2015) - [i3]Soumith Chintala, Marc'Aurelio Ranzato, Arthur Szlam, Yuandong Tian, Mark Tygert, Wojciech Zaremba:
Scale-invariant learning and convolutional networks. CoRR abs/1506.08230 (2015) - [i2]Yan Zhu, Yuandong Tian, Dimitris N. Metaxas, Piotr Dollár:
Semantic Amodal Segmentation. CoRR abs/1509.01329 (2015) - [i1]Bolei Zhou, Yuandong Tian, Sainbayar Sukhbaatar, Arthur Szlam, Rob Fergus:
Simple Baseline for Visual Question Answering. CoRR abs/1512.02167 (2015) - 2013
- [b1]Yuandong Tian:
Theory and Practice of Globally Optimal Deformation Estimation. Carnegie Mellon University, USA, 2013 - [c14]Nan Li, Yuandong Tian, William W. Cohen, Kenneth R. Koedinger:
Integrating Perceptual Learning with External World Knowledge in a Simulated Student. AIED 2013: 400-410 - [c13]Yuandong Tian, Srinivasa G. Narasimhan:
Hierarchical Data-Driven Descent for Efficient Optimal Deformation Estimation. ICCV 2013: 2288-2295 - 2012
- [j2]Mohit Gupta, Yuandong Tian, Srinivasa G. Narasimhan, Li Zhang:
A Combined Theory of Defocused Illumination and Global Light Transport. Int. J. Comput. Vis. 98(2): 146-167 (2012) - [j1]Yuandong Tian, Srinivasa G. Narasimhan:
Globally Optimal Estimation of Nonrigid Image Distortion. Int. J. Comput. Vis. 98(3): 279-302 (2012) - [c12]Yuandong Tian, Srinivasa G. Narasimhan, Alan Van Nevel:
Depth from optical turbulence. CVPR 2012: 246-253 - [c11]Yuandong Tian, C. Lawrence Zitnick, Srinivasa G. Narasimhan:
Exploring the Spatial Hierarchy of Mixture Models for Human Pose Estimation. ECCV (5) 2012: 256-269 - [c10]Yuandong Tian, Jun Zhu:
Learning from crowds in the presence of schools of thought. KDD 2012: 226-234 - 2011
- [c9]Yuandong Tian, Srinivasa G. Narasimhan:
Rectification and 3D reconstruction of curved document images. CVPR 2011: 377-384 - [c8]Dong Huang, Yuandong Tian, Fernando De la Torre:
Local isomorphism to solve the pre-image problem in kernel methods. CVPR 2011: 2761-2768 - 2010
- [c7]Yuandong Tian, Srinivasa G. Narasimhan:
A globally optimal data-driven approach for image distortion estimation. CVPR 2010: 1277-1284
2000 – 2009
- 2009
- [c6]Mohit Gupta, Yuandong Tian, Srinivasa G. Narasimhan, Li Zhang:
(De) focusing on global light transport for active scene recovery. CVPR 2009: 2969-2976 - [c5]Yuandong Tian, Srinivasa G. Narasimhan:
Seeing through water: Image restoration using model-based tracking. ICCV 2009: 2303-2310 - 2008
- [c4]Shifeng Chen, Yuandong Tian, Fang Wen, Ying-Qing Xu, Xiaoou Tang:
Easytoon: an easy and quick tool to personalize a cartoon storyboard using family photo album. ACM Multimedia 2008: 499-508 - 2007
- [c3]Jingyu Cui, Fang Wen, Rong Xiao, Yuandong Tian, Xiaoou Tang:
EasyAlbum: an interactive photo annotation system based on face clustering and re-ranking. CHI 2007: 367-376 - [c2]Yuandong Tian, Wei Liu, Rong Xiao, Fang Wen, Xiaoou Tang:
A Face Annotation Framework with Partial Clustering and Interactive Labeling. CVPR 2007 - 2006
- [c1]Rong Xiao, Wu-Jun Li, Yuandong Tian, Xiaoou Tang:
Joint Boosting Feature Selection for Robust Face Recognition. CVPR (2) 2006: 1415-1422
Coauthor Index
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