Tian, Yuandong

115 publications

NeurIPS 2025 AdvPrefix: An Objective for Nuanced LLM Jailbreaks Sicheng Zhu, Brandon Amos, Yuandong Tian, Chuan Guo, Ivan Evtimov

ICML 2025 AdvPrompter: Fast Adaptive Adversarial Prompting for LLMs Anselm Paulus, Arman Zharmagambetov, Chuan Guo, Brandon Amos, Yuandong Tian

ICML 2025 Agent-as-a-Judge: Evaluate Agents with Agents Mingchen Zhuge, Changsheng Zhao, Dylan R. Ashley, Wenyi Wang, Dmitrii Khizbullin, Yunyang Xiong, Zechun Liu, Ernie Chang, Raghuraman Krishnamoorthi, Yuandong Tian, Yangyang Shi, Vikas Chandra, Jürgen Schmidhuber

NeurIPS 2025 Composing Global Solutions to Reasoning Tasks via Algebraic Objects in Neural Nets Yuandong Tian

ICLR 2025 Dualformer: Controllable Fast and Slow Thinking by Learning with Randomized Reasoning Traces DiJia Su, Sainbayar Sukhbaatar, Michael Rabbat, Yuandong Tian, Qinqing Zheng

ICML 2025 From Low Rank Gradient Subspace Stabilization to Low-Rank Weights: Observations, Theories, and Applications Ajay Kumar Jaiswal, Yifan Wang, Lu Yin, Shiwei Liu, Runjin Chen, Jiawei Zhao, Ananth Grama, Yuandong Tian, Zhangyang Wang

ICML 2025 GSM-$∞$: How Do Your LLMs Behave over Infinitely Increasing Reasoning Complexity and Context Length? Yang Zhou, Hongyi Liu, Zhuoming Chen, Yuandong Tian, Beidi Chen

ICLR 2025 MagicPIG: LSH Sampling for Efficient LLM Generation Zhuoming Chen, Ranajoy Sadhukhan, Zihao Ye, Yang Zhou, Jianyu Zhang, Niklas Nolte, Yuandong Tian, Matthijs Douze, Leon Bottou, Zhihao Jia, Beidi Chen

NeurIPS 2025 NaturalReasoning: Reasoning in the Wild with 2.8m Challenging Questions Weizhe Yuan, Jane Yu, Song Jiang, Karthik Padthe, Yang Li, Dong Wang, Ilia Kulikov, Kyunghyun Cho, Yuandong Tian, Jason E Weston, Xian Li

ICLR 2025 Param$\Delta$ for Direct Mixing: Post-Train Large Language Model at Zero Cost Sheng Cao, Mingrui Wu, Karthik Prasad, Yuandong Tian, Zechun Liu

NeurIPS 2025 ParetoQ: Improving Scaling Laws in Extremely Low-Bit LLM Quantization Zechun Liu, Changsheng Zhao, Hanxian Huang, Sijia Chen, Jing Zhang, Jiawei Zhao, Scott Roy, Lisa Jin, Yunyang Xiong, Yangyang Shi, Lin Xiao, Yuandong Tian, Bilge Soran, Raghuraman Krishnamoorthi, Tijmen Blankevoort, Vikas Chandra

CPAL 2025 Q-GaLore: Quantized GaLore with INT4 Projection and Layer-Adaptive Low-Rank Gradients Zhenyu Zhang, Ajay Kumar Jaiswal, Lu Yin, Shiwei Liu, Jiawei Zhao, Yuandong Tian, Zhangyang Wang

ICLR 2025 R-Sparse: Rank-Aware Activation Sparsity for Efficient LLM Inference Zhenyu Zhang, Zechun Liu, Yuandong Tian, Harshit Khaitan, Zhangyang Wang, Steven Li

NeurIPS 2025 Reasoning by Superposition: A Theoretical Perspective on Chain of Continuous Thought Hanlin Zhu, Shibo Hao, Zhiting Hu, Jiantao Jiao, Stuart Russell, Yuandong Tian

ICLR 2025 Sail into the Headwind: Alignment via Robust Rewards and Dynamic Labels Against Reward Hacking Paria Rashidinejad, Yuandong Tian

ICLRW 2025 Spectral Journey: How Transformers Predict the Shortest Path Andrew Cohen, Andrey Gromov, Kaiyu Yang, Yuandong Tian

ICLR 2025 SpinQuant: LLM Quantization with Learned Rotations Zechun Liu, Changsheng Zhao, Igor Fedorov, Bilge Soran, Dhruv Choudhary, Raghuraman Krishnamoorthi, Vikas Chandra, Yuandong Tian, Tijmen Blankevoort

ICML 2025 Token Assorted: Mixing Latent and Text Tokens for Improved Language Model Reasoning Dijia Su, Hanlin Zhu, Yingchen Xu, Jiantao Jiao, Yuandong Tian, Qinqing Zheng

ICLR 2025 Towards General-Purpose Model-Free Reinforcement Learning Scott Fujimoto, Pierluca D'Oro, Amy Zhang, Yuandong Tian, Michael Rabbat

ICLRW 2025 Training Large Language Models to Reason in a Continuous Latent Space Shibo Hao, Sainbayar Sukhbaatar, DiJia Su, Xian Li, Zhiting Hu, Jason E Weston, Yuandong Tian

ICLRW 2024 Beyond A*: Better Planning with Transformers via Search Dynamics Bootstrapping Lucas Lehnert, Sainbayar Sukhbaatar, Paul McVay, Michael Rabbat, Yuandong Tian

NeurIPSW 2024 Composing Global Optimizers to Reasoning Tasks via Algebraic Objects in Neural Nets Yuandong Tian

ICML 2024 Contrastive Predict-and-Search for Mixed Integer Linear Programs Taoan Huang, Aaron M Ferber, Arman Zharmagambetov, Yuandong Tian, Bistra Dilkina

NeurIPSW 2024 Crafting Global Optimizers to Reasoning Tasks via Algebraic Objects in Neural Nets Yuandong Tian

ICLR 2024 Efficient Streaming Language Models with Attention Sinks Guangxuan Xiao, Yuandong Tian, Beidi Chen, Song Han, Mike Lewis

ICML 2024 GaLore: Memory-Efficient LLM Training by Gradient Low-Rank Projection Jiawei Zhao, Zhenyu Zhang, Beidi Chen, Zhangyang Wang, Anima Anandkumar, Yuandong Tian

ICLRW 2024 GaLore: Memory-Efficient LLM Training by Gradient Low-Rank Projection Jiawei Zhao, Zhenyu Zhang, Beidi Chen, Zhangyang Wang, Anima Anandkumar, Yuandong Tian

ICML 2024 GenCO: Generating Diverse Designs with Combinatorial Constraints Aaron M Ferber, Arman Zharmagambetov, Taoan Huang, Bistra Dilkina, Yuandong Tian

ICLR 2024 H-GAP: Humanoid Control with a Generalist Planner Zhengyao Jiang, Yingchen Xu, Nolan Wagener, Yicheng Luo, Michael Janner, Edward Grefenstette, Tim Rocktäschel, Yuandong Tian

ICLR 2024 JoMA: Demystifying Multilayer Transformers via Joint Dynamics of MLP and Attention Yuandong Tian, Yiping Wang, Zhenyu Zhang, Beidi Chen, Simon Shaolei Du

ICML 2024 LoCoCo: Dropping in Convolutions for Long Context Compression Ruisi Cai, Yuandong Tian, Zhangyang Wang, Beidi Chen

NeurIPSW 2024 MagicPIG: LSH Sampling for Efficient LLM Generation Zhuoming Chen, Ranajoy Sadhukhan, Zihao Ye, Yang Zhou, Jianyu Zhang, Niklas Nolte, Yuandong Tian, Matthijs Douze, Leon Bottou, Zhihao Jia, Beidi Chen

ICML 2024 MobileLLM: Optimizing Sub-Billion Parameter Language Models for On-Device Use Cases Zechun Liu, Changsheng Zhao, Forrest Iandola, Chen Lai, Yuandong Tian, Igor Fedorov, Yunyang Xiong, Ernie Chang, Yangyang Shi, Raghuraman Krishnamoorthi, Liangzhen Lai, Vikas Chandra

NeurIPS 2024 On the Surprising Effectiveness of Attention Transfer for Vision Transformers Alexander C. Li, Yuandong Tian, Beidi Chen, Deepak Pathak, Xinlei Chen

ICLR 2024 RLCD: Reinforcement Learning from Contrastive Distillation for LM Alignment Kevin Yang, Dan Klein, Asli Celikyilmaz, Nanyun Peng, Yuandong Tian

NeurIPSW 2024 Tensor-GaLore: Memory-Efficient Training via Gradient Tensor Decomposition Robert Joseph George, David Pitt, Jiawei Zhao, Jean Kossaifi, Cheng Luo, Yuandong Tian, Anima Anandkumar

NeurIPSW 2024 Towards Full Delegation: Designing Ideal Agentic Behaviors for Travel Planning Song Jiang, Da Ju, Andrew Cohen, Sasha Mitts, Aaron Foss, Justine T Kao, Xian Li, Yuandong Tian

NeurIPS 2024 Towards a Theoretical Understanding of the 'Reversal Curse' via Training Dynamics Hanlin Zhu, Baihe Huang, Shaolun Zhang, Michael Jordan, Jiantao Jiao, Yuandong Tian, Stuart Russell

ICML 2024 TravelPlanner: A Benchmark for Real-World Planning with Language Agents Jian Xie, Kai Zhang, Jiangjie Chen, Tinghui Zhu, Renze Lou, Yuandong Tian, Yanghua Xiao, Yu Su

ICLRW 2024 TravelPlanner: A Benchmark for Real-World Planning with Language Agents Jian Xie, Kai Zhang, Jiangjie Chen, Tinghui Zhu, Renze Lou, Yuandong Tian, Yanghua Xiao, Yu Su

NeurIPSW 2023 Contrastive Predict-and-Search for Mixed Integer Linear Programs Taoan Huang, Aaron M Ferber, Arman Zharmagambetov, Yuandong Tian, Bistra Dilkina

ICML 2023 Deja Vu: Contextual Sparsity for Efficient LLMs at Inference Time Zichang Liu, Jue Wang, Tri Dao, Tianyi Zhou, Binhang Yuan, Zhao Song, Anshumali Shrivastava, Ce Zhang, Yuandong Tian, Christopher Re, Beidi Chen

ICLR 2023 Efficient Planning in a Compact Latent Action Space Zhengyao Jiang, Tianjun Zhang, Michael Janner, Yueying Li, Tim Rocktäschel, Edward Grefenstette, Yuandong Tian

ICLRW 2023 EurNet: Efficient Multi-Range Relational Modeling of Protein Structure Minghao Xu, Yuanfan Guo, Yi Xu, Jian Tang, Xinlei Chen, Yuandong Tian

NeurIPSW 2023 H-GAP: Humanoid Control with a Generalist Planner Zhengyao Jiang, Yingchen Xu, Nolan Wagener, Yicheng Luo, Michael Janner, Edward Grefenstette, Tim Rocktäschel, Yuandong Tian

NeurIPS 2023 H2O: Heavy-Hitter Oracle for Efficient Generative Inference of Large Language Models Zhenyu Zhang, Ying Sheng, Tianyi Zhou, Tianlong Chen, Lianmin Zheng, Ruisi Cai, Zhao Song, Yuandong Tian, Christopher Ré, Clark Barrett, Zhangyang "Atlas" Wang, Beidi Chen

ICMLW 2023 H2O: Heavy-Hitter Oracle for Efficient Generative Inference of Large Language Models Zhenyu Zhang, Ying Sheng, Tianyi Zhou, Tianlong Chen, Lianmin Zheng, Ruisi Cai, Zhao Song, Yuandong Tian, Christopher Re, Clark Barrett, Zhangyang Wang, Beidi Chen

NeurIPSW 2023 JoMA: Demystifying Multilayer Transformers via JOint Dynamics of MLP and Attention Yuandong Tian, Yiping Wang, Zhenyu Zhang, Beidi Chen, Simon Du

NeurIPS 2023 Landscape Surrogate: Learning Decision Losses for Mathematical Optimization Under Partial Information Arman Zharmagambetov, Brandon Amos, Aaron Ferber, Taoan Huang, Bistra Dilkina, Yuandong Tian

ICMLW 2023 Landscape Surrogate: Learning Decision Losses for Mathematical Optimization Under Partial Information Arman Zharmagambetov, Brandon Amos, Aaron M Ferber, Taoan Huang, Bistra Dilkina, Yuandong Tian

ICMLW 2023 Landscape Surrogate: Learning Decision Losses for Mathematical Optimization Under Partial Information Arman Zharmagambetov, Brandon Amos, Aaron M Ferber, Taoan Huang, Bistra Dilkina, Yuandong Tian

ICML 2023 Learning Compiler Pass Orders Using Coreset and Normalized Value Prediction Youwei Liang, Kevin Stone, Ali Shameli, Chris Cummins, Mostafa Elhoushi, Jiadong Guo, Benoit Steiner, Xiaomeng Yang, Pengtao Xie, Hugh James Leather, Yuandong Tian

ICLR 2023 MACTA: A Multi-Agent Reinforcement Learning Approach for Cache Timing Attacks and Detection Jiaxun Cui, Xiaomeng Yang, Mulong Luo, Geunbae Lee, Peter Stone, Hsien-Hsin S. Lee, Benjamin Lee, G. Edward Suh, Wenjie Xiong, Yuandong Tian

NeurIPS 2023 Scan and Snap: Understanding Training Dynamics and Token Composition in 1-Layer Transformer Yuandong Tian, Yiping Wang, Beidi Chen, Simon S Du

ICML 2023 Searching Large Neighborhoods for Integer Linear Programs with Contrastive Learning Taoan Huang, Aaron M Ferber, Yuandong Tian, Bistra Dilkina, Benoit Steiner

ICMLW 2023 Searching Large Neighborhoods for Integer Linear Programs with Contrastive Learning Taoan Huang, Aaron M Ferber, Yuandong Tian, Bistra Dilkina, Benoit Steiner

ICML 2023 SurCo: Learning Linear SURrogates for COmbinatorial Nonlinear Optimization Problems Aaron M Ferber, Taoan Huang, Daochen Zha, Martin Schubert, Benoit Steiner, Bistra Dilkina, Yuandong Tian

ICMLW 2023 SurCo: Learning Linear SURrogates for COmbinatorial Nonlinear Optimization Problems Aaron M Ferber, Taoan Huang, Daochen Zha, Martin Schubert, Benoit Steiner, Bistra Dilkina, Yuandong Tian

TMLR 2023 Understanding Curriculum Learning in Policy Optimization for Online Combinatorial Optimization Runlong Zhou, Zelin He, Yuandong Tian, Yi Wu, Simon Shaolei Du

ICLR 2023 Understanding the Role of Nonlinearity in Training Dynamics of Contrastive Learning Yuandong Tian

AISTATS 2022 Provably Efficient Policy Optimization for Two-Player Zero-Sum Markov Games Yulai Zhao, Yuandong Tian, Jason Lee, Simon Du

ICML 2022 Denoised MDPs: Learning World Models Better than the World Itself Tongzhou Wang, Simon Du, Antonio Torralba, Phillip Isola, Amy Zhang, Yuandong Tian

NeurIPS 2022 DreamShard: Generalizable Embedding Table Placement for Recommender Systems Daochen Zha, Louis Feng, Qiaoyu Tan, Zirui Liu, Kwei-Herng Lai, Bhargav Bhushanam, Yuandong Tian, Arun Kejariwal, Xia Hu

NeurIPSW 2022 Efficient Planning in a Compact Latent Action Space Zhengyao Jiang, Tianjun Zhang, Michael Janner, Yueying Li, Tim Rocktäschel, Edward Grefenstette, Yuandong Tian

AAAI 2022 Learning Bounded Context-Free-Grammar via LSTM and the Transformer: Difference and the Explanations Hui Shi, Sicun Gao, Yuandong Tian, Xinyun Chen, Jishen Zhao

ICLR 2022 Multi-Objective Optimization by Learning Space Partition Yiyang Zhao, Linnan Wang, Kevin Yang, Tianjun Zhang, Tian Guo, Yuandong Tian

ICLR 2022 NASViT: Neural Architecture Search for Efficient Vision Transformers with Gradient Conflict Aware Supernet Training Chengyue Gong, Dilin Wang, Meng Li, Xinlei Chen, Zhicheng Yan, Yuandong Tian, Qiang Liu, Vikas Chandra

CVPR 2022 On the Importance of Asymmetry for Siamese Representation Learning Xiao Wang, Haoqi Fan, Yuandong Tian, Daisuke Kihara, Xinlei Chen

NeurIPSW 2022 Understanding Curriculum Learning in Policy Optimization for Online Combinatorial Optimization Runlong Zhou, Yuandong Tian, Yi Wu, Simon Shaolei Du

NeurIPS 2022 Understanding Deep Contrastive Learning via Coordinate-Wise Optimization Yuandong Tian

ICLR 2022 Understanding Dimensional Collapse in Contrastive Self-Supervised Learning Li Jing, Pascal Vincent, Yann LeCun, Yuandong Tian

AISTATS 2021 Understanding Robustness in Teacher-Student Setting: A New Perspective Zhuolin Yang, Zhaoxi Chen, Tiffany Cai, Xinyun Chen, Bo Li, Yuandong Tian

CVPR 2021 FBNetV3: Joint Architecture-Recipe Search Using Predictor Pretraining Xiaoliang Dai, Alvin Wan, Peizhao Zhang, Bichen Wu, Zijian He, Zhen Wei, Kan Chen, Yuandong Tian, Matthew Yu, Peter Vajda, Joseph E. Gonzalez

CVPR 2021 FP-NAS: Fast Probabilistic Neural Architecture Search Zhicheng Yan, Xiaoliang Dai, Peizhao Zhang, Yuandong Tian, Bichen Wu, Matt Feiszli

ICML 2021 Few-Shot Neural Architecture Search Yiyang Zhao, Linnan Wang, Yuandong Tian, Rodrigo Fonseca, Tian Guo

NeurIPS 2021 Latent Execution for Neural Program Synthesis Beyond Domain-Specific Languages Xinyun Chen, Dawn Song, Yuandong Tian

ICML 2021 Learn-to-Share: A Hardware-Friendly Transfer Learning Framework Exploiting Computation and Parameter Sharing Cheng Fu, Hanxian Huang, Xinyun Chen, Yuandong Tian, Jishen Zhao

NeurIPS 2021 Learning Space Partitions for Path Planning Kevin Yang, Tianjun Zhang, Chris Cummins, Brandon Cui, Benoit Steiner, Linnan Wang, Joseph E Gonzalez, Dan Klein, Yuandong Tian

NeurIPS 2021 MADE: Exploration via Maximizing Deviation from Explored Regions Tianjun Zhang, Paria Rashidinejad, Jiantao Jiao, Yuandong Tian, Joseph E Gonzalez, Stuart J. Russell

NeurIPS 2021 NovelD: A Simple yet Effective Exploration Criterion Tianjun Zhang, Huazhe Xu, Xiaolong Wang, Yi Wu, Kurt Keutzer, Joseph E Gonzalez, Yuandong Tian

ICML 2021 Understanding Self-Supervised Learning Dynamics Without Contrastive Pairs Yuandong Tian, Xinlei Chen, Surya Ganguli

ICLR 2020 Deep Symbolic Superoptimization Without Human Knowledge Hui Shi, Yang Zhang, Xinyun Chen, Yuandong Tian, Jishen Zhao

NeurIPS 2020 Joint Policy Search for Multi-Agent Collaboration with Imperfect Information Yuandong Tian, Qucheng Gong, Yu Jiang

NeurIPS 2020 Learning Search Space Partition for Black-Box Optimization Using Monte Carlo Tree Search Linnan Wang, Rodrigo Fonseca, Yuandong Tian

AAAI 2020 Neural Architecture Search Using Deep Neural Networks and Monte Carlo Tree Search Linnan Wang, Yiyang Zhao, Yuu Jinnai, Yuandong Tian, Rodrigo Fonseca

ICLR 2020 Playing the Lottery with Rewards and Multiple Languages: Lottery Tickets in RL and NLP Haonan Yu, Sergey Edunov, Yuandong Tian, Ari S. Morcos

ICML 2020 Student Specialization in Deep Rectified Networks with Finite Width and Input Dimension Yuandong Tian

ICLR 2019 Algorithmic Framework for Model-Based Deep Reinforcement Learning with Theoretical Guarantees Yuping Luo, Huazhe Xu, Yuanzhi Li, Yuandong Tian, Trevor Darrell, Tengyu Ma

NeurIPS 2019 Coda: An End-to-End Neural Program Decompiler Cheng Fu, Huili Chen, Haolan Liu, Xinyun Chen, Yuandong Tian, Farinaz Koushanfar, Jishen Zhao

ICML 2019 ELF OpenGo: An Analysis and Open Reimplementation of AlphaZero Yuandong Tian, Jerry Ma, Qucheng Gong, Shubho Sengupta, Zhuoyuan Chen, James Pinkerton, Larry Zitnick

NeurIPS 2019 Hierarchical Decision Making by Generating and Following Natural Language Instructions Hengyuan Hu, Denis Yarats, Qucheng Gong, Yuandong Tian, Mike Lewis

NeurIPS 2019 Learning to Perform Local Rewriting for Combinatorial Optimization Xinyun Chen, Yuandong Tian

ICLR 2019 M^3RL: Mind-Aware Multi-Agent Management Reinforcement Learning Tianmin Shu, Yuandong Tian

NeurIPS 2019 One Ticket to Win Them All: Generalizing Lottery Ticket Initializations Across Datasets and Optimizers Ari Morcos, Haonan Yu, Michela Paganini, Yuandong Tian

ICMLW 2019 Real-World Video Adaptation with Reinforcement Learning Hongzi Mao, Shannon Chen, Drew Dimmery, Shaun Singh, Drew Blaisdell, Yuandong Tian, Mohammad Alizadeh, Eytan Bakshy

WACV 2018 Channel-Recurrent Autoencoding for Image Modeling Wenling Shang, Kihyuk Sohn, Yuandong Tian

ICML 2018 Gradient Descent Learns One-Hidden-Layer CNN: Don’t Be Afraid of Spurious Local Minima Simon Du, Jason Lee, Yuandong Tian, Aarti Singh, Barnabas Poczos

ICLR 2018 When Is a Convolutional Filter Easy to Learn? Simon S. Du, Jason D. Lee, Yuandong Tian

ICML 2017 An Analytical Formula of Population Gradient for Two-Layered ReLU Network and Its Applications in Convergence and Critical Point Analysis Yuandong Tian

NeurIPS 2017 ELF: An Extensive, Lightweight and Flexible Research Platform for Real-Time Strategy Games Yuandong Tian, Qucheng Gong, Wenling Shang, Yuxin Wu, C. Lawrence Zitnick

CVPR 2017 Semantic Amodal Segmentation Yan Zhu, Yuandong Tian, Dimitris Metaxas, Piotr Dollar

ICLR 2017 Symmetry-Breaking Convergence Analysis of Certain Two-Layered Neural Networks with ReLU Nonlinearity Yuandong Tian

ICLR 2017 Training Agent for First-Person Shooter Game with Actor-Critic Curriculum Learning Yuxin Wu, Yuandong Tian

ICLR 2016 Better Computer Go Player with Neural Network and Long-Term Prediction Yuandong Tian, Yan Zhu

ECCV 2016 Single Image 3D Interpreter Network Jiajun Wu, Tianfan Xue, Joseph J. Lim, Yuandong Tian, Joshua B. Tenenbaum, Antonio Torralba, William T. Freeman

ICCV 2013 Hierarchical Data-Driven Descent for Efficient Optimal Deformation Estimation Yuandong Tian, Srinivasa G. Narasimhan

CVPR 2012 Depth from Optical Turbulence Yuandong Tian, Srinivasa G. Narasimhan, Alan Van Nevel

ECCV 2012 Exploring the Spatial Hierarchy of Mixture Models for Human Pose Estimation Yuandong Tian, C. Lawrence Zitnick, Srinivasa G. Narasimhan

CVPR 2011 Local Isomorphism to Solve the Pre-Image Problem in Kernel Methods Dong Huang, Yuandong Tian, Fernando De la Torre

CVPR 2011 Rectification and 3D Reconstruction of Curved Document Images Yuandong Tian, Srinivasa G. Narasimhan

CVPR 2010 A Globally Optimal Data-Driven Approach for Image Distortion Estimation Yuandong Tian, Srinivasa G. Narasimhan

CVPR 2009 (De) Focusing on Global Light Transport for Active Scene Recovery Mohit Gupta, Yuandong Tian, Srinivasa G. Narasimhan, Li Zhang

ICCV 2009 Seeing Through Water: Image Restoration Using Model-Based Tracking Yuandong Tian, Srinivasa G. Narasimhan

CVPR 2007 A Face Annotation Framework with Partial Clustering and Interactive Labeling Yuandong Tian, Wei Liu, Rong Xiao, Fang Wen, Xiaoou Tang

CVPR 2006 Joint Boosting Feature Selection for Robust Face Recognition Rong Xiao, Wu-Jun Li, Yuandong Tian, Xiaoou Tang