Publications (^* indicates equal contributions, and ^‡ indicates advisees)

• Tell Your Model Where to Attend: Post-hoc Attention Steering for LLMs
  Qingru Zhang^‡, Chandan Singh, Liyuan Liu, Xiaodong Liu, Bin Yu, Jianfeng Gao, Tuo Zhao
  International Conference on Learning Representations (ICLR), 2024 [arXiv]
  
• LoftQ: LoRA-Fine-Tuning-Aware Quantization for Large Language Models
  Yixiao Li^‡, Yifan Yu^‡, Chen Liang^‡, Pengcheng He, Nikos Karampatziakis, Weizhu Chen and Tuo Zhao
  International Conference on Learning Representations (ICLR), 2024 [arXiv]
  
• Deep Nonparametric Estimation of Operators between Infinite Dimensional Spaces
  Hao Liu, Haizhao Yang, Minshuo Chen^‡, Tuo Zhao and Wenjing Liao
  Accepted by Journal of Machine Learning Research (JMLR), 2024[arXiv]
  
• Efficient Long-Range Transformers: You Need to Attend More, but Not Necessarily at Every Layer
  Qingru Zhang^‡, Dhananjay Ram, Cole Hawkins, Sheng Zha and Tuo Zhao
  Conference on Empirical Methods in Natural Language Processing (EMNLP), 2023 [arXiv]
  
• HadSkip: Homotopic and Adaptive Layer Skipping of Pre-trained Language Models for Efficient Inference
  Haoyu Wang, Yaqing Wang, Tianci Liu, Tuo Zhao and Jing Gao
  Conference on Empirical Methods in Natural Language Processing (EMNLP), 2023
  
• Robust Multi-Agent Reinforcement Learning via Adversarial Regularization: Theoretical Foundation and Stable Algorithms
  Alexander Bukharin^‡, Yan Li^‡, Yue Yu, Qingru Zhang^‡, Zhehui Chen^‡, Simiao Zuo^‡, Chao Zhang, Songan Zhang and Tuo Zhao
  Annual Conference on Neural Information Processing (NeurIPS), 2023 [arXiv]
  
• Module-wise Adaptive Distillation for Multimodality Foundation Models
  Chen Liang^‡, Jiahui Yu, Ming-Hsuan Yang, Matthew Brown, Yin Cui, Tuo Zhao, Boqing Gong and Tianyi Zhou
  Annual Conference on Neural Information Processing (NeurIPS), 2023 [arXiv]
  
• Model-Based Reparameterization Policy Gradient Methods: Theory and Practical Algorithms
  Shenao Zhang, Boyi Liu, Zhaoran Wang and Tuo Zhao
  Annual Conference on Neural Information Processing (NeurIPS), 2023
  
• Pivotal Estimation of Linear Discriminant Analysis in High Dimensions
  Ethan Fang, Yajun Mei, Yuyang Shi, Qunzhi Xu and Tuo Zhao
  Journal of Machine Learning Research (JMLR), 2023+ [arXiv]
  
• High Dimensional Binary Classification under Label Shift: Phase Transition and Regularization
  Jiahui Cheng*, Minshuo Chen^*‡, Hao Liu, Tuo Zhao and Wenjing Liao
  Sampling Theory, Signal Processing, and Data Analysis, 2023+ [arXiv]
  
• Homotopic Policy Mirror Descent: Policy Convergence, Implicit Regularization, and Improved Sample Complexity
  Yan Li^‡, George Lan and Tuo Zhao
  Mathematical Programming Series Series A, 2023+ [arXiv]
  
• LightToken: a Task and Model-agnostic Lightweight Token Embedding Framework for Pre-trained Language Models
  Haoyu Wang, Ruirui Li, Haoming Jiang, Zhengyang Wang, Xianfeng Tang, Bin Bi, Monica Cheng, Bing Yin, Yaqing Wang, Tuo Zhao and Jing Gao
  SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), 2023 [arXiv]
  
• County augmented transformer for COVID‐19 state hospitalizations prediction
  Siawpeng Er^‡, Shihao Yang and Tuo Zhao
  Scientific Reports, 2023 [arXiv]
  
• Context-Aware Query Rewriting for Improving Users' Search Experience on E-commerce Websites
  Simiao Zuo^‡, Qingyu Yin, Haoming Jiang, Shaohui Xi, Bing Yin, Chao Zhang and Tuo Zhao
  Annual Meeting of the Association for Computational Linguistics (ACL), 2023 [arXiv]
  
• Effective Minkowski Dimension of Deep Nonparametric Regression: Function Approximation and Statistical Theories
  Zixuan Zhang^‡, Minshuo Chen^‡, Mengdi Wang, Wenjing Liao and Tuo Zhao
  International Conference on Machine Learning (ICML), 2023 [arXiv]
  
• Machine Learning Force Fields with Data Cost Aware Training
  Alexander Bukharin^‡, Tianyi Liu, Shengjie Wang, Simiao Zuo^‡, Weihao Gao, Wen Yan and Tuo Zhao
  International Conference on Machine Learning (ICML), 2023 [arXiv]
  
• SMURF-THP: Score Matching-based UnceRtainty quantiFication for Transformer Hawkes Process
  Zichong Li^‡, Yanbo Xu, Simiao Zuo^‡, Haoming Jiang, Chao Zhang, Tuo Zhao and Hongyuan Zha
  International Conference on Machine Learning (ICML), 2023 [arXiv]
  
• LoSparse: Structured Compression of Large Language Models based on Low-Rank and Sparse Approximation
  Yixiao Li*^‡, Yifan Yu*^‡, Qingru Zhang^‡, Chen Liang^‡, Pengcheng He, Weizhu Chen and Tuo Zhao
  International Conference on Machine Learning (ICML), 2023 [arXiv]
  
• Score Approximation, Estimation and Distribution Recovery of Diffusion Models on Low-Dimensional Data
  Minshuo Chen^‡, Kaixuan Huang, Tuo Zhao and Mengdi Wang
  International Conference on Machine Learning (ICML), 2023 [arXiv]
  
• Less is More: Task-aware Layer-wise Distillation for Language Model Compression
  Chen Liang^‡, Simiao Zuo^‡, Qingru Zhang^‡, Pengcheng He, Weizhu Chen and Tuo Zhao
  International Conference on Machine Learning (ICML), 2023 [arXiv]
  
• Learning Generalizable Vision-Tactile Robotic Grasping Strategy for Deformable Objects via Transformer
  Yunhai Han, Rahul Batra, Nathan Boyd, Tuo Zhao, Yu She, Seth Hutchinson and Ye Zhao
  International Conference on Advanced Intelligent Mechatronics (AIM), 2023 [arXiv]
  
• A Manifold Two-Sample Test Study: Integral Probability Metric with Neural Networks
  Jie Wang, Minshuo Chen^‡, Tuo Zhao, Wenjing Liao and Yao Xie
  Information and Inference: A Journal of the IMA, 2023 [arXiv]
  
• Sample Complexity of Nonparametric Off-Policy Evaluation on Low-Dimensional Manifolds using Deep Networks
  Xiang Ji, Minshuo Chen^‡, Mengdi Wang and Tuo Zhao
  International Conference on Learning Representations (ICLR), 2023 [arXiv]
  
• Adaptive Budget Allocation for Parameter-Efficient Fine-Tuning
  Qingru Zhang^‡, Minshuo Chen^‡, Alexander Bukharin^‡, Pengcheng He, Yu Cheng, Weizhu Chen and Tuo Zhao
  International Conference on Learning Representations (ICLR), 2023 [arXiv]
  
• HomoDistil: Homotopic Task-Agnostic Distillation of Pre-trained Transformers
  Chen Liang^‡, Haoming Jiang, Zheng Li, Xianfeng Tang, Bing Yin and Tuo Zhao
  International Conference on Learning Representations (ICLR), 2023 [arXiv]
  
• Reinforcement Learning for Adaptive Mesh Refinement
  Jiachen Yang^‡, Tarik Dzanic, Brenden Petersen, Jun Kudo, Ketan Mittal, Vladimir Tomov, Jean-Sylvain Camier, Tuo Zhao, Hongyuan Zha, Tzanio Kolev, Robert Anderson and Daniel Faissol
  International Conference on Artificial Intelligence and Statistics (AISTATS), 2023 [arXiv]
  
• Block Policy Mirror Descent
  George Lan, Yan Li^‡ and Tuo Zhao
  Tentatively Accepted to SIAM Journal on Optimization (SIOPT), 2023+ [arXiv]
  
• On Deep Generative Models for Approximation and Estimation of Distributions on Manifolds
  Biraj Dahal, Alexander Havrilla, Minshuo Chen^‡, Tuo Zhao and Wenjing Liao
  Annual Conference on Neural Information Processing (NeurIPS)，2022 [arXiv]
  
• Benefits of Overparameterized Convolutional Residual Networks: Function Approximation under Smoothness Constraint
  Hao Liu, Minshuo Chen^‡, Siawpeng Er^‡, Wenjing Liao, Tong Zhang and Tuo Zhao
  International Conference on Machine Learning (ICML), 2022 [arXiv]
  
• PLATON: Pruning Large Transformer Models with Upper Confidence Bound of Weight Importance
  Qingru Zhang^‡, Simiao Zuo^‡, Chen Liang^‡, Alex Bukharin^‡, Pengcheng He, Weizhu Chen and Tuo Zhao
  International Conference on Machine Learning (ICML), 2022 [arXiv]
  
• MoEBERT: from BERT to Mixture-of-Experts via Importance-Guided Adaptation
  Simiao Zuo^‡, Qingru Zhang^‡, Chen Liang^‡, Pengcheng He, Tuo Zhao and Weizhu Chen
  Annual Conference of the North American Chapter of the Association for Computational Linguistics (NAACL), 2022 [arXiv]
  
• CERES: Pretraining of Graph-Conditioned Transformer for Semi-Structured Session Data
  Rui Feng, Chen Luo, Qingyu Yin, Bing Yin, Tuo Zhao and Chao Zhang
  Annual Conference of the North American Chapter of the Association for Computational Linguistics (NAACL), 2022 [arXiv]
  
• Self-Training with Differentiable Teacher
  Simiao Zuo^‡, Yue Yu, Chen Liang, Haoming Jiang, Siawpeng Er, Chao Zhang Tuo Zhao and Hongyuan Zha
  Annual Conference of the North American Chapter of the Association for Computational Linguistics (NAACL), 2022 [arXiv]
  
• Adversarially Regularized Policy Learning Guided by Trajectory Optimization
  Zhigen Zhao, Simiao Zuo^‡, Tuo Zhao and Ye Zhao
  Annual Learning for Dynamics & Control Conference (L4DC), 2022 [arXiv]
  
• CAMERO: Consistency Regularized Ensemble of Perturbed Language Models with Weight Sharing
  Chen Liang^‡, Pengcheng He, Yelong Shen, Weizhu Chen and Tuo Zhao
  Annual Meeting of the Association for Computational Linguistics (ACL), 2022 [arXiv]
  
• No Parameters Left Behind: Sensitivity Guided Adaptive Learning Rate for Training Large Transformer Models
  Chen Liang^‡, Haoming Jiang^‡, Simiao Zuo^‡, Pengcheng He, Xiaodong Liu, Jianfeng Gao, Weizhu Chen and Tuo Zhao
  International Conference on Learning Representations (ICLR), 2022 [arXiv]
  
• Frequency-aware SGD for Efficient Embedding Learning with Provable Benefits
  Yan Li^‡, Dhruv Choudhary, Xiaohan Wei, Baichuan Yuan, Bhargav Bhushanam, Tuo Zhao and Guanghui Lan
  International Conference on Learning Representations (ICLR), 2022 [arXiv]
  
• Taming Sparsely Activated Transformer with Stochastic Experts
  Simiao Zuo^‡, Xiaodong Liu, Jian Jiao, Young Jin Kim, Hany Hassan, Ruofei Zhang, Tuo Zhao and Jianfeng Gao
  International Conference on Learning Representations (ICLR), 2022 [arXiv]
  
• Large Learning Rate Tames Homogeneity: Convergence and Balancing Effect
  Yuqing Wang, Minshuo Chen^‡, Tuo Zhao and Molei Tao
  International Conference on Learning Representations (ICLR), 2022 [arXiv]
  
• Noise Regularizes Over-parameterized Rank One Matrix Recovery, Provably
  Tianyi Liu^‡, Yan Li^‡, Enlu Zhou and Tuo Zhao
  International Conference on Artificial Intelligence and Statistics (AISTATS), 2022 [arXiv]
  
• Adaptive Incentive Design with Multi-Agent Meta-Gradient Reinforcement Learning
  Jiachen Yang^‡, Ethan Wang^‡, Rakshit Trivedi, Tuo Zhao and Hongyuan Zha
  International Conference on Autonomous Agents and Multiagent Systems, 2022 [arXiv]
  
• Nonparametric Regression on Low-Dimensional Manifolds using Deep ReLU Networks
  Minshuo Chen^‡, Haoming Jiang^‡, Wenjing Liao and Tuo Zhao (Alphabetical order)
  Information and Inference: A Journal of the IMA, 2022 [arXiv, Poster]
  
• Pessimism Meets Invariance: Provably Efficient Offline Mean-Field Multi-Agent RL
  Minshuo Chen^‡, Yan Li^‡, Zhuoran Yang, Zhaoran Wang and Tuo Zhao
  Annual Conference on Neural Information Processing (NeurIPS)，2021 [arXiv]
  
• Towards Automatic Evaluation of Dialog Systems: A Model-Free Off-Policy Evaluation Approach
  Haoming Jiang^‡, Bo Dai, Mengjiao Yang, Tuo Zhao and Wei Wei
  Conference on Empirical Methods in Natural Language Processing (EMNLP)，2021 [arXiv]
  
• Adversarial Training as Stackelberg Game: An Unrolled Optimization Approach
  Simiao Zuo^‡, Chen Liang^‡, Haoming Jiang^‡, Xiaodong Liu, Pengcheng He, Weizhu Chen, Jianfeng Gao and Tuo Zhao
  Conference on Empirical Methods in Natural Language Processing (EMNLP)，2021 [arXiv]
  
• Token-wise Curriculum Learning for Neural Machine Translation
  Chen Liang^‡, Haoming Jiang^‡, Xiaodong Liu, Pengcheng He, Weizhu Chen, Jianfeng Gao and Tuo Zhao
  Conference on Empirical Methods in Natural Language Processing (EMNLP)，2021 [arXiv]
  
• ARCH: Efficient Adversarial Regularized Training with Caching
  Simiao Zuo^‡, Chen Liang^‡, Haoming Jiang^‡, Xiaodong Liu, Pengcheng He, Weizhu Chen, Jianfeng Gao and Tuo Zhao
  Conference on Empirical Methods in Natural Language Processing (EMNLP)，2021
  
• QUEACO: Query Attribute Value Extraction in E-commerce
  Danqing Zhang, Zheng Li, Tianyu Cao, Chen Luo, Tony Wu, Yiwei Song, Bing Yin, Tuo Zhao and Qiang Yang
  ACM International Conference on Information and Knowledge Management (CIKM), 2021 [arXiv]
  
• A Diffusion Approximation Theory of Momentum SGD in Nonconvex Optimization
  Tianyi Liu^‡, Zhehui Chen^‡, Enlu Zhou and Tuo Zhao
  Stochastic Systems (Accepted), 2021+ [arXiv, Poster]
  
• COUnty aggRegation mixup AuGmEntation (COURAGE) COVID-19 Prediction
  Siawpeng Er^‡, Shihao Yang and Tuo Zhao
  Scientific Reports [arXiv]
  
• Besov Function Approximation and Binary Classification on Low-Dimensional Manifolds Using Convolutional Residual Networks
  Hao Liu, Minshuo Chen^‡, Tuo Zhao and Wenjing Liao
  International Conference on Machine Learning (ICML), 2021 [arXiv]
  
• How Important is the Train-Validation Split in Meta-Learning?
  Yu Bai, Minshuo Chen^‡, Pan Zhou, Tuo Zhao, Jason D. Lee, Sham Kakade, Huan Wang and Caiming Xiong
  International Conference on Machine Learning (ICML), 2021 [arXiv]
  
• Super Tickets in Pre-Trained Language Models: From Model Compression to Improving Generalization
  Chen Liang^‡, Simiao Zuo^‡, Minshuo Chen^‡, Haoming Jiang^‡, Xiaodong Liu, Pengcheng He, Tuo Zhao and Weizhu Chen
  Annual Meeting of the Association for Computational Linguistics (ACL), 2021 [arXiv]
  
• Named Entity Recognition with Small Strongly Labeled and Large Weakly Labeled Data
  Haoming Jiang^‡, Danqing Zhang, Tianyu Cao, Bing Yin and Tuo Zhao
  Annual Meeting of the Association for Computational Linguistics (ACL), 2021 [arXiv]
  
• Fine-Tuning Pre-trained Language Models with Weak Supervision: A Contrastive-Regularized Self-Training Approach
  Yue Yu*, Simiao Zuo^‡*, Haoming Jiang^‡, Wendi Ren, Tuo Zhao and Chao Zhang
  Annual Conference of the North American Chapter of the Association for Computational Linguistics (NAACL), 2021 [arXiv]
  
• Deep Learning Assisted End-to-End Synthesis of mm-Wave Passive Networks with 3D EM Structures: A Study on A Transformer-Based Matching Network
  Siawpeng Er^‡, Edward Liu, Minshuo Chen^‡, Yan Li^‡, Yuqi Liu, Tuo Zhao and Hua Wang
  International Microwave Symposium (IMS), 2021
  
• Learning to Defend by Learning to Attack
  Haoming Jiang^*‡, Zhehui Chen^*‡, Yuyang Shi, Bo Dai and Tuo Zhao
  International Conference on Artificial Intelligence and Statistics (AISTATS), 2021 [arXiv, Poster]
  
• Noisy Gradient Descent Converges to Flat Minima for Nonconvex Matrix Factorization
  Tianyi Liu^‡, Yan Li^‡, Song Wei, Enlu Zhou and Tuo Zhao
  International Conference on Artificial Intelligence and Statistics (AISTATS), 2021
  
• A Hypergradient Approach to Robust Regression without Correspondence
  Yujia Xie^‡*, Yixiu Mao*, Simiao Zuo^‡, Hongteng Xu, Xiaojing Ye, Tuo Zhao and Hongyuan Zha
  International Conference on Learning Representations (ICLR), 2021 [arXiv]
  
• Spectrum Truncation Power Iteration for Agnostic Matrix Phase Retrieval
  Lewis Liu, Songtao Lu, Tuo Zhao and Zhaoran Wang
  IEEE Transactions on Signal Processing (Accepted with Minor Revisions), 2021+
  
• Towards Understanding Hierarchical Learning: Benefits of Neural Representations
  Minshuo Chen^*‡, Yu Bai, Jason Lee, Tuo Zhao, Huan Wang, Caiming Xiong and Richard Socher
  Annual Conference on Neural Information Processing Systems (NeurIPS), 2020 [arXiv, Poster]
  
• Why Do Deep Residual Networks Generalize Better than Deep Feedforward Networks? -- A Neural Tangent Kernel Perspective
  Kaixuan Huang^*‡, Yuqing Wang*, Molei Tao and Tuo Zhao
  Annual Conference on Neural Information Processing Systems (NeurIPS), 2020 [arXiv]
  
• Differentiable Top-k Operator with Optimal Transport
  Yujia Xie^‡, Hanjun Dai, Minshuo Chen^‡, Bo Dai, Tuo Zhao, Hongyuan Zha, Wei Wei and Tomas Pfister
  Annual Conference on Neural Information Processing Systems (NeurIPS), 2020 [arXiv]
  
• Calibrated Fine-Tuning for Pre-trained Language Models via Manifold Smoothing
  Lingkai Kong, Haoming Jiang^‡, Yuchen Zhuang, Jie Lyu, Tuo Zhao and Chao Zhang
  Conference on Empirical Methods in Natural Language Processing (EMNLP), 2020
  
• Deep Reinforcement Learning with Smooth Policy
  Qianli Shen^*‡, Yan Li^*‡, Haoming Jiang^‡, Zhaoran Wang and Tuo Zhao
  International Conference on Machine Learning (ICML), 2020 [arXiv]
  
• Transformer Hawkes Process
  Simiao Zuo^‡, Haoming Jiang^‡, Zichong Li^‡, Tuo Zhao and Hongyuan Zha
  International Conference on Machine Learning (ICML), 2020 [arXiv]
  
• BOND: Bert-Assisted Open-Domain Named Entity Recognition with Distant Supervision
  Chen Liang^*‡, Yue Yu^*, Haoming Jiang^*‡, Siawpeng Er, Ruijia Wang, Tuo Zhao and Chao Zhang
  SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), 2020
  
• SMART: Robust and Efficient Fine-Tuning for Pre-trained Natural Language Models through Principled Regularized Optimization
  Haoming Jiang^‡, Pengcheng He, Weizhu Chen, Xiaodong Liu, Jianfeng Gao and Tuo Zhao
  Annual Meeting of the Association for Computational Linguistics (ACL), 2020 [arXiv]
  
• Multi-Domain Neural Machine Translation with Word-Level Adaptive Layer-wise Domain Mixing
  Haoming Jiang^*‡, Chen Liang^*‡, Chong Wang and Tuo Zhao
  Annual Meeting of the Association for Computational Linguistics (ACL), 2020 [arXiv, Poster]
  
• Residual Network Based Direct Synthesis of EM Structures: A Study on One-to-One Transformers.
  David Munzer, Minshuo Chen^‡, Siawpeng Er, Yan Li^‡, Naga Mannem, Tuo Zhao and Hua Wang
  IEEE Radio Frequency Integrated Circuits Symposium (RFIC), 2020
  
• On Generalization Bounds of a Family of Recurrent Neural Networks
  Minshuo Chen^‡, Xingguo Li^‡ and Tuo Zhao
  International Conference on Artificial Intelligence and Statistics (AISTATS), 2020 [arXiv, Poster]
  
• Implicit Bias of Gradient Descent based Adversarial Training on Separable Data
  Yan Li^‡, Ethan Fang, Huan Xu and Tuo Zhao
  International Conference on Learning Representations (ICLR), 2020 [arXiv, Poster]
  
• On Computation and Generalization of Generative Adversarial Imitation Learning
  Minshuo Chen^‡, Yizhou Wang^‡, Tianyi Liu^‡, Zhuoran Yang, Xingguo Li^‡, Zhaoran Wang and Tuo Zhao
  International Conference on Learning Representations (ICLR), 2020 [arXiv, Poster]
  
• Efficient Approximation of Deep ReLU Networks for Functions on Low Dimensional Manifolds
  Minshuo Chen^‡, Haoming Jiang^‡, Wenjing Liao and Tuo Zhao (Alphabetical order)
  Annual Conference on Neural Information Processing Systems (NeurIPS), 2019 [arXiv, Poster]
  
• Meta Learning with Relational Information for Short Sequences
  Yujia Xie^‡, Haoming Jiang^‡, Feng Liu^‡, Tuo Zhao and Hongyuan Zha
  Annual Conference on Neural Information Processing Systems (NeurIPS), 2019 [arXiv, Poster]
  
• Towards Understanding the Importance of Shortcut Connections in Residual Networks
  Tianyi Liu^*‡, Minshuo Chen^*‡, Mo Zhou^‡, Simon Du, Enlu Zhou and Tuo Zhao
  Annual Conference on Neural Information Processing Systems (NeurIPS), 2019 [arXiv, Poster]
  
• Online Factorization and Partition of Complex Networks From Random Walks
  Lin Yang^‡, Vladimir Braverman, Tuo Zhao and Mengdi Wang
  Annual Conference on Uncertainty in Artificial Intelligence (UAI), 2019 [arXiv, Poster]
  
• On Fast Convergence of Proximal Algorithms for SQRT-Lasso Optimization: Don't Worry About Its Nonsmooth Loss Function
  Xingguo Li^‡, Haoming Jiang^‡, Jarvis Haupt, Raman Arora, Han Liu, Mingyi Hong and Tuo Zhao
  Annual Conference on Uncertainty in Artificial Intelligence (UAI), 2019 [arXiv, Software, Poster]
  
• Towards Understanding the Importance of Noise in Training Neural Networks
  Mo Zhou^*‡, Tianyi Liu^*‡, Yan Li^‡, Dachao Lin, Enlu Zhou and Tuo Zhao
  International Conference on Machine Learning (ICML), 2019 [arXiv, Poster]
  
• On Scalable and Efficient Computation of Large Scale Optimal Transport
  Yujia Xie^‡, Minshuo Chen^‡, Haoming Jiang^‡, Tuo Zhao and Hongyuan Zha
  International Conference on Machine Learning (ICML), 2019 [arXiv, Poster]
  
• On Landscape of Lagrangian Functions and Stochastic Search for Constrained Nonconvex Optimization
  Zhehui Chen^*‡, Xingguo Li^*‡, Lin Yang^‡, Jarvis Haupt and Tuo Zhao
  International Conference on Artificial Intelligence and Statistics (AISTATS), 2019 [arXiv, Poster]
  
• On Computation and Generalization of Generative Adversarial Networks under Spectrum Control
  Haoming Jiang^‡, Zhehui Chen^‡, Minshuo Chen^‡, Feng Liu^‡, Dingding Wang and Tuo Zhao
  International Conference on Learning Representations (ICLR), 2019 [arXiv, Poster]
  
• Picasso: A Sparse Learning Library for High Dimensional Data Analysis in R and Python
  Jason Ge^*‡, Xingguo Li^*‡, Haoming Jiang^‡, Han Liu, Tong Zhang, Mengdi Wang and Tuo Zhao
  Journal of Machine Learning Research (JMLR), 20(44):1−5, 2019 [PDF, Software]
  [2016 ASA Best Student Paper Award on Statistical Computing]
  
• Misspecified Nonconvex Statitical Optimization for Sparse Phase Retrival
  Zhuoran Yang^*, Lin Yang^*‡, Ethan Fang, Tuo Zhao, Zhaoran Wang and Matey Neykov
  Mathematical Programming Series Series B, 176(1-2):1-27, 2019 [arXiv]
  
• Symmetry, Saddle Points and Global Optimization Landscape of Nonconvex Matrix Factorization
  Xingguo Li^‡, Junwei Lu, Raman Arora, Jarvis Haupt, Han Liu, Zhaoran Wang and Tuo Zhao
  IEEE Transactions on Information Theory, 65(6):3489-3514, 2019 [arXiv]
  
• Dimensionality Reduction for Stationary Time Series via Stochastic Nonconvex Optimization
  Minshuo Chen^‡, Lin Yang^‡, Mengdi Wang and Tuo Zhao
  Annual Conference on Neural Information Processing Systems (NeurIPS), 2018 [arXiv]
  
• Towards Understanding Acceleration Tradeoff between Momentum and Asynchrony in Distributed Nonconvex Stochastic Optimization
  Tianyi Liu^‡, Shiyang Li^‡, Jianping Shi, Enlu Zhou and Tuo Zhao
  Annual Conference on Neural Information Processing Systems (NeurIPS), 2018 [arXiv]
  
• Physical Systems behind Optimization Algorithms
  Lin Yang^‡, Raman Arora, Vladimir Braverman and Tuo Zhao
  Annual Conference on Neural Information Processing Systems (NeurIPS), 2018 [arXiv]
  
• Provable Gaussian Embedding with One Observation
  Ming Yu, Zhuoran Yang, Tuo Zhao, Mladen Kolar and Zhaoran Wang
  Annual Conference on Neural Information Processing Systems (NeurIPS), 2018 [arXiv]
  
• On Local Quadratic Convergence of DC Proximal Newton Algorithm for Nonconvex Regularized Sparse Learning in High Dimensions
  Xingguo Li^‡, Lin Yang^‡, Jason Ge^‡, Jarvis Haupt, Tong Zhang and Tuo Zhao
  Annual Conference on Neural Information Processing Systems (NeurIPS), 2017 [arXiv]
  
• Deep Hyperspherical Learning
  Weiyang Liu, Yan-Ming Zhang, Xingguo Li, Zhiding Yu, Bo Dai, Tuo Zhao and Le Song
  Annual Conference on Neural Information Processing Systems (NeurIPS), 2017 [arXiv]
  
• Homotopy Parametric Simplex Method for Sparse Learning
  Haotian Pang, Robert Vanderbei, Han Liu and Tuo Zhao
  Annual Conference on Neural Information Processing Systems (NeurIPS), 2017 [arXiv]
  
• On Faster Convergence of Cyclic Block Coordinate Descent-type Methods for Strongly Convex Minimization
  Xingguo Li^*, Tuo Zhao^*, Raman Arora, Han Liu and Mingyi Hong
  Journal of Machine Learning Research (JMLR), 18(4):1-24 2018 [arXiv]
  International Conference on Artificial Intelligence and Statistics (AISTATS), 2016 (short version)
  
• Online Multiview Learning: Dropping Convexity for Better Efficiency
  Zhehui Chen^‡, Lin Yang^‡, Chris Li and Tuo Zhao
  International Conference on Machine Learning (ICML), 2017 [arXiv]
  
• Pathwise Coordinate Optimization for Nonconvex Sparse Learning: Algorithm and Theory
  Tuo Zhao, Han Liu and Tong Zhang
  The Annals of Statistics, 46(1):180-218, 2018 [arXiv, Software]
  
• NESTT: A Nonconvex Primal-Dual Splitting Method for Distributed and Stochastic Optimization
  Davood Hajinezhad, Mingyi Hong, Tuo Zhao and Zhaoran Wang
  Annual Conference on Neural Information Processing Systems (NeurIPS), 2016 [arXiv]
  
• Stochastic Variance Reduced Optimization for Nonconvex Sparse Learning
  Xingguo Li^*, Tuo Zhao^*, Raman Arora, Han Liu and Jarvis Haupt
  International Conference on Machine Learning (ICML), 2016 [arXiv]
  
• Accelerated Path-following Iterative Shrinkage Thresholding Algorithm
  Tuo Zhao and Han Liu
  Journal of Computational and Graphical Statistics (JCGS), 25(4):1272-1296, 2016 [PDF]
  
• A Nonconvex Optimization Framework for Low Rank Matrix Factorization
  Tuo Zhao, Zhaoran Wang and Han Liu
  Annual Conference on Neural Information Processing Systems (NeurIPS), 2015 [PDF]
  
• Calibrated Multivariate Regression with Application to Neural Semantic Basis Discovery
  Han Liu, Lie Wang and Tuo Zhao (Alphabetical order)
  Journal of Machine Learning Research (JMLR), 16(8):1579−1606, 2015 [PDF, Software]
  Annual Conference on Neural Information Processing Systems (NeurIPS), 2014 (short version)
  [2016 INFORMS SAS Best Paper Award on Data Mining]
  
• The "flare" Package for High-dimensional Sparse Linear Regression in R
  Xinguo Li^*, Tuo Zhao^*, Xiaoming Yuan and Han Liu
  Journal of Machine Learning Research (JMLR), 16(3):553-557, 2015 [Software, Vignette, PDF]
  
• Accelerated Mini-batch Randomized Coordinate Descent Method
  Tuo Zhao^*, Mo Yu^*, Yiming Wang, Raman Arora and Han Liu
  Annual Conference on Neural Information Processing Systems (NeurIPS), 2014 [PDF]
  
• Calibrated Precision Matrix Estimation for High Dimensional Elliptical Distributions
  Tuo Zhao and Han Liu
  IEEE Transactions on Information Theory, 60(12):7874-7887, 2014 [PDF]
  Annual Conference on Neural Information Processing Systems (NeurIPS) 2013 (short version)
  
• Positive Semidefinite Rank-based Correlation Matrix Estimation with Application to Semiparametric Graph Estimation
  Tuo Zhao, Kathryn Roeder and Han Liu
  Journal of Computational and Graphical Statistics (JCGS), 23(4):895-922, 2014 [PDF]
  Annual Conference on Neural Information Processing Systems (NeurIPS) 2012 (short version)
  
• Sparse Covariance Matrix Estimation with Eigenvalue Constraints
  Han Liu, Lie Wang and Tuo Zhao (Alphabetical order)
  Journal of Computational and Graphical Statistics (JCGS), 23(2):439-459, 2014 [PDF]
  
• CODA: High Dimensional Copula Discriminant Analysis
  Fang Han, Tuo Zhao and Han Liu
  Journal of Machine Learning Research (JMLR), 14(2):629-671, 2013 [PDF]
  
• Automated Diagnoses of Attention Deficit Hyperactive Disorder using Magnetic Resonance Imaging
  Ani Eloyan, Tuo Zhao, et al.
  Frontiers in Systems Neuroscience, 6(61):1-9, 2012 [PDF, Winner of INDI ADHD-200 Global Competition]
  
• Patterns and rates of exonic de novo mutations in autism spectrum disorders
  Benjamin Neale, Tuo Zhao, et al.
  Nature, 485:242-245, 2012 [PDF, News from New York Times]
  
• The "huge" Package for High-dimensional Undirected Graph Estimation in R
  Tuo Zhao, Han Liu, Kathryn Roeder, John Lafferty and Larry Wasserman
  Journal of Machine Learning Research (JMLR),13(4):1059-1062, 2012 [PDF, Software, Vignette]
  
• Sparse Additive Machine
  Tuo Zhao and Han Liu
  International Conference on Artificial Intelligence and Statistics (AISTATS), 2012 [PDF, Software]