Tuo Zhao - RankMe

294 papers A* 57A 15B 1C 4Misc 3Journal 171Unranked 43

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	AMR-Net: Adaptive Temporal-Channel Multiresolution Network for Industrial Time-Series Prediction. IEEE Trans. Ind. Informatics Haiteng Wang, Lei Ren, Tuo Zhao
2026	J	`jnl`	Approximation of Log-Partition Function in Policy Mirror Descent Induces Implicit Regularization for LLM Post-Training. CoRR Zhenghao Xu, Qin Lu, Changlong Yu, Tuo Zhao
2026	J	`jnl`	CoLLM: Industrial Large-Small Model Collaboration With Fuzzy Decision-Making Agent and Self-Reflection. IEEE Trans. Fuzzy Syst. Haiteng Wang, Lei Ren, Tuo Zhao, Lu Jiao
2026	J	`jnl`	Diffusion Model for Manifold Data: Score Decomposition, Curvature, and Statistical Complexity. CoRR Zixuan Zhang, Kaixuan Huang, Tuo Zhao, Mengdi Wang, Minshuo Chen
2026	J	`jnl`	Teach Diffusion Language Models to Learn from Their Own Mistakes. CoRR Liming Liu, Binxuan Huang, Xin Liu, Bing Yin, Tuo Zhao
2026	—	`conf`	Tidal: Tackling Concept Drift in Provenance-Based Advanced Persistent Threats Detection. NINeS Yajie Zhou, Nengneng Yu, Tuo Zhao, Zaoxing Liu
2025	J	`jnl`	A Minimalist Example of Edge-of-Stability and Progressive Sharpening. CoRR Liming Liu, Zixuan Zhang, Simon S. Du, Tuo Zhao
2025	J	`jnl`	ARMOR: High-Performance Semi-Structured Pruning via Adaptive Matrix Factorization. CoRR Lawrence Liu, Alexander Liu, Mengdi Wang, Tuo Zhao, Lin F. Yang
2025	J	`jnl`	AdaSPEC: Selective Knowledge Distillation for Efficient Speculative Decoders. CoRR Yuezhou Hu, Jiaxin Guo, Xinyu Feng, Tuo Zhao
2025	J	`jnl`	Adversarial Training of Reward Models. CoRR Alexander Bukharin, Haifeng Qian, Shengyang Sun, Adithya Renduchintala, Soumye Singhal, Zhilin Wang, Oleksii Kuchaiev, Olivier Delalleau, Tuo Zhao
2025	J	`jnl`	Ask a Strong LLM Judge when Your Reward Model is Uncertain. CoRR Zhenghao Xu, Qin Lu, Qingru Zhang, Liang Qiu, Ilgee Hong, Changlong Yu, Wenlin Yao, Yao Liu, Haoming Jiang, Lihong Li, Hyokun Yun, Tuo Zhao
2025	J	`jnl`	COSMOS: A Hybrid Adaptive Optimizer for Memory-Efficient Training of LLMs. CoRR Liming Liu, Zhenghao Xu, Zixuan Zhang, Hao Kang, Zichong Li, Chen Liang, Weizhu Chen, Tuo Zhao
2025	—	`conf`	DORM: Preference Data Weights Optimization for Reward Modeling in LLM Alignment. EMNLP (Findings) Rongzhi Zhang, Chenwei Zhang, Xinyang Zhang, Liang Qiu, Haoming Jiang, Yuchen Zhuang, Qingru Zhang, Hyokun Yun, Xian Li, Bing Yin, Tuo Zhao, Chao Zhang
2025	A*	`conf`	Deep Reinforcement Learning from Hierarchical Preference Design. ICML Alexander Bukharin, Yixiao Li, Pengcheng He, Tuo Zhao
2025	A*	`conf`	Discriminative Finetuning of Generative Large Language Models without Reward Models and Human Preference Data. ICML Siqi Guo, Ilgee Hong, Vicente Balmaseda, Changlong Yu, Liang Qiu, Xin Liu, Haoming Jiang, Tuo Zhao, Tianbao Yang
2025	J	`jnl`	Discriminative Finetuning of Generative Large Language Models without Reward Models and Preference Data. CoRR Siqi Guo, Ilgee Hong, Vicente Balmaseda, Tuo Zhao, Tianbao Yang
2025	J	`jnl`	FDformer: A Fuzzy Dynamic Transformer-Based Network for Efficient Industrial Time Series Prediction. IEEE Trans. Fuzzy Syst. Lei Ren, Tuo Zhao, Haiteng Wang
2025	J	`jnl`	Good regularity creates large learning rate implicit biases: edge of stability, balancing, and catapult. J. Mach. Learn. Res. Yuqing Wang, Zhenghao Xu, Tuo Zhao, Molei Tao
2025	J	`jnl`	IDEA Prune: An Integrated Enlarge-and-Prune Pipeline in Generative Language Model Pretraining. CoRR Yixiao Li, Xianzhi Du, Ajay Jaiswal, Tao Lei, Tuo Zhao, Chong Wang, Jianyu Wang
2025	J	`jnl`	LLMs Can Generate a Better Answer by Aggregating Their Own Responses. CoRR Zichong Li, Xinyu Feng, Yuheng Cai, Zixuan Zhang, Tianyi Liu, Chen Liang, Weizhu Chen, Haoyu Wang, Tuo Zhao
2025	Misc	`conf`	MS-RainMamba: Learning Multi-Scale State Space Models for Single Image Deraining. ICASSP Haibo Li, Zhanshuo Liu, Tuo Zhao, Tingting Zhao, Yarui Chen, Ning Xie
2025	J	`jnl`	NoWag: A Unified Framework for Shape Preserving Compression of Large Language Models. CoRR Lawrence Liu, Inesh Chakrabarti, Yixiao Li, Mengdi Wang, Tuo Zhao, Lin F. Yang
2025	J	`jnl`	NorMuon: Making Muon more efficient and scalable. CoRR Zichong Li, Liming Liu, Chen Liang, Weizhu Chen, Tuo Zhao
2025	J	`jnl`	OpenRubrics: Towards Scalable Synthetic Rubric Generation for Reward Modeling and LLM Alignment. CoRR Tianci Liu, Ran Xu, Tony Yu, Ilgee Hong, Carl Yang, Tuo Zhao, Haoyu Wang
2025	—	`conf`	RoseRAG: Robust Retrieval-augmented Generation with Small-scale LLMs via Margin-aware Preference Optimization. ACL (Findings) Tianci Liu, Haoxiang Jiang, Tianze Wang, Ran Xu, Yue Yu, Linjun Zhang, Tuo Zhao, Haoyu Wang
2025	J	`jnl`	RoseRAG: Robust Retrieval-augmented Generation with Small-scale LLMs via Margin-aware Preference Optimization. CoRR Tianci Liu, Haoxiang Jiang, Tianze Wang, Ran Xu, Yue Yu, Linjun Zhang, Tuo Zhao, Haoyu Wang
2025	J	`jnl`	Self-Rewarding PPO: Aligning Large Language Models with Demonstrations Only. CoRR Qingru Zhang, Liang Qiu, Ilgee Hong, Zhenghao Xu, Tianyi Liu, Shiyang Li, Rongzhi Zhang, Zheng Li, Lihong Li, Bing Yin, Chao Zhang, Jianshu Chen, Haoming Jiang, Tuo Zhao
2025	J	`jnl`	SlimMoE: Structured Compression of Large MoE Models via Expert Slimming and Distillation. CoRR Zichong Li, Chen Liang, Zixuan Zhang, Ilgee Hong, Young Jin Kim, Weizhu Chen, Tuo Zhao
2025	J	`jnl`	The influences of four dimensions of perceived fit on individuals' utilisation of SPOCs: an extension of the task-technology fit model. Behav. Inf. Technol. Lin Zhang, Zhen Shao, Tuo Zhao, Kuanchin Chen
2025	J	`jnl`	Think-RM: Enabling Long-Horizon Reasoning in Generative Reward Models. CoRR Ilgee Hong, Changlong Yu, Liang Qiu, Weixiang Yan, Zhenghao Xu, Haoming Jiang, Qingru Zhang, Qin Lu, Xin Liu, Chao Zhang, Tuo Zhao
2024	C	`conf`	A Cloud-Edge Intelligent Collaborative Framework and Its Applications in AIGC and Digital Twins. IECON Haiteng Wang, Lu Jiao, Tuo Zhao, Lei Ren
2024	A*	`conf`	Adaptive Preference Scaling for Reinforcement Learning with Human Feedback. NeurIPS Ilgee Hong, Zichong Li, Alexander Bukharin, Yixiao Li, Haoming Jiang, Tianbao Yang, Tuo Zhao
2024	J	`jnl`	Adaptive Preference Scaling for Reinforcement Learning with Human Feedback. CoRR Ilgee Hong, Zichong Li, Alexander Bukharin, Yixiao Li, Haoming Jiang, Tianbao Yang, Tuo Zhao
2024	A*	`conf`	Beyond Point Prediction: Score Matching-based Pseudolikelihood Estimation of Neural Marked Spatio-Temporal Point Process. ICML Zichong Li, Qunzhi Xu, Zhenghao Xu, Yajun Mei, Tuo Zhao, Hongyuan Zha
2024	A*	`conf`	BlendFilter: Advancing Retrieval-Augmented Large Language Models via Query Generation Blending and Knowledge Filtering. EMNLP Haoyu Wang, Ruirui Li, Haoming Jiang, Jinjin Tian, Zhengyang Wang, Chen Luo, Xianfeng Tang, Monica Xiao Cheng, Tuo Zhao, Jing Gao
2024	J	`jnl`	BlendFilter: Advancing Retrieval-Augmented Large Language Models via Query Generation Blending and Knowledge Filtering. CoRR Haoyu Wang, Tuo Zhao, Jing Gao
2024	—	`conf`	Data Diversity Matters for Robust Instruction Tuning. EMNLP (Findings) Alexander Bukharin, Shiyang Li, Zhengyang Wang, Jingfeng Yang, Bing Yin, Xian Li, Chao Zhang, Tuo Zhao, Haoming Jiang
2024	J	`jnl`	Deep Nonparametric Estimation of Operators between Infinite Dimensional Spaces. J. Mach. Learn. Res. Hao Liu, Haizhao Yang, Minshuo Chen, Tuo Zhao, Wenjing Liao
2024	J	`jnl`	Digitally-enabled antecedents of trust, repurchase intention and the impact of blockchain traceability labels. Electron. Commer. Res. Appl. Lin Zhang, Zhen Shao, Tuo Zhao, Xiaotong Li, Jianfeng Zhang
2024	—	`conf`	GEAR: An Efficient Error Reduction Framework for KV Cache Compression in LLM Inference. ENLSP Hao Kang, Qingru Zhang, Souvik Kundu, Geonhwa Jeong, Zaoxing Liu, Tushar Krishna, Tuo Zhao
2024	J	`jnl`	GEAR: An Efficient KV Cache Compression Recipe for Near-Lossless Generative Inference of LLM. CoRR Hao Kang, Qingru Zhang, Souvik Kundu, Geonhwa Jeong, Zaoxing Liu, Tushar Krishna, Tuo Zhao
2024	J	`jnl`	Homotopic policy mirror descent: policy convergence, algorithmic regularization, and improved sample complexity. Math. Program. Yan Li, Guanghui Lan, Tuo Zhao
2024	—	`conf`	Hybrid Deep Generative and Sequential Learning Approach for Stock Market Prediction. ICIC (LNAI 5) Tuo Zhao, Xinxue Wang, Tingting Zhao, Yuan Wang, Yarui Chen, JuCheng Yang
2024	J	`jnl`	Learning explainable task-relevant state representation for model-free deep reinforcement learning. Neural Networks Tingting Zhao, Guixi Li, Tuo Zhao, Yarui Chen, Ning Xie, Gang Niu, Masashi Sugiyama
2024	A*	`conf`	LoftQ: LoRA-Fine-Tuning-aware Quantization for Large Language Models. ICLR Yixiao Li, Yifan Yu, Chen Liang, Nikos Karampatziakis, Pengcheng He, Weizhu Chen, Tuo Zhao
2024	J	`jnl`	Model Tells Itself Where to Attend: Faithfulness Meets Automatic Attention Steering. CoRR Qingru Zhang, Xiaodong Yu, Chandan Singh, Xiaodong Liu, Liyuan Liu, Jianfeng Gao, Tuo Zhao, Dan Roth, Hao Cheng
2024	A*	`conf`	Nonparametric Classification on Low Dimensional Manifolds using Overparameterized Convolutional Residual Networks. NeurIPS Zixuan Zhang, Kaiqi Zhang, Minshuo Chen, Yuma Takeda, Mengdi Wang, Tuo Zhao, Yu-Xiang Wang
2024	A*	`conf`	Provable Acceleration of Nesterov's Accelerated Gradient for Asymmetric Matrix Factorization and Linear Neural Networks. NeurIPS Zhenghao Xu, Yuqing Wang, Tuo Zhao, Rachel Ward, Molei Tao
2024	J	`jnl`	Provable Acceleration of Nesterov's Accelerated Gradient for Rectangular Matrix Factorization and Linear Neural Networks. CoRR Zhenghao Xu, Yuqing Wang, Tuo Zhao, Rachel Ward, Molei Tao
2024	J	`jnl`	RNR: Teaching Large Language Models to Follow Roles and Rules. CoRR Kuan Wang, Alexander Bukharin, Haoming Jiang, Qingyu Yin, Zhengyang Wang, Tuo Zhao, Jingbo Shang, Chao Zhang, Bing Yin, Xian Li, Jianshu Chen, Shiyang Li
2024	A*	`conf`	Robust Reinforcement Learning from Corrupted Human Feedback. NeurIPS Alexander Bukharin, Ilgee Hong, Haoming Jiang, Zichong Li, Qingru Zhang, Zixuan Zhang, Tuo Zhao
2024	J	`jnl`	Robust Reinforcement Learning from Corrupted Human Feedback. CoRR Alexander Bukharin, Ilgee Hong, Haoming Jiang, Qingru Zhang, Zixuan Zhang, Tuo Zhao
2024	A*	`conf`	RoseLoRA: Row and Column-wise Sparse Low-rank Adaptation of Pre-trained Language Model for Knowledge Editing and Fine-tuning. EMNLP Haoyu Wang, Tianci Liu, Ruirui Li, Monica Xiao Cheng, Tuo Zhao, Jing Gao
2024	J	`jnl`	RoseLoRA: Row and Column-wise Sparse Low-rank Adaptation of Pre-trained Language Model for Knowledge Editing and Fine-tuning. CoRR Haoyu Wang, Tianci Liu, Tuo Zhao, Jing Gao
2024	J	`jnl`	Sample Complexity of Neural Policy Mirror Descent for Policy Optimization on Low-Dimensional Manifolds. J. Mach. Learn. Res. Zhenghao Xu, Xiang Ji, Minshuo Chen, Mengdi Wang, Tuo Zhao
2024	J	`jnl`	Stochastic Constrained Decentralized Optimization for Machine Learning with Fewer Data Oracles: a Gradient Sliding Approach. CoRR Hoang Huy Nguyen, Yan Li, Tuo Zhao
2024	A*	`conf`	Tell Your Model Where to Attend: Post-hoc Attention Steering for LLMs. ICLR Qingru Zhang, Chandan Singh, Liyuan Liu, Xiaodong Liu, Bin Yu, Jianfeng Gao, Tuo Zhao
2024	A*	`conf`	To Cool or not to Cool? Temperature Network Meets Large Foundation Models via DRO. ICML Zi-Hao Qiu, Siqi Guo, Mao Xu, Tuo Zhao, Lijun Zhang, Tianbao Yang
2024	J	`jnl`	To Cool or not to Cool? Temperature Network Meets Large Foundation Models via DRO. CoRR Zi-Hao Qiu, Siqi Guo, Mao Xu, Tuo Zhao, Lijun Zhang, Tianbao Yang
2024	—	`conf`	Trust in Digital Commerce: the Moderating Effect of Blockchain Teability Labels. PACIS Zhen Shao, Tuo Zhao, Lin Zhang, Yu Liu
2023	A*	`conf`	Adaptive Budget Allocation for Parameter-Efficient Fine-Tuning. ICLR Qingru Zhang, Minshuo Chen, Alexander Bukharin, Pengcheng He, Yu Cheng, Weizhu Chen, Tuo Zhao
2023	J	`jnl`	Adaptive Budget Allocation for Parameter-Efficient Fine-Tuning. CoRR Qingru Zhang, Minshuo Chen, Alexander Bukharin, Pengcheng He, Yu Cheng, Weizhu Chen, Tuo Zhao
2023	J	`jnl`	Block Policy Mirror Descent. SIAM J. Optim. Guanghui Lan, Yan Li, Tuo Zhao
2023	—	`conf`	Context-Aware Query Rewriting for Improving Users' Search Experience on E-commerce Websites. ACL (industry) Simiao Zuo, Qingyu Yin, Haoming Jiang, Shaohui Xi, Bing Yin, Chao Zhang, Tuo Zhao
2023	J	`jnl`	Data Diversity Matters for Robust Instruction Tuning. CoRR Alexander Bukharin, Tuo Zhao
2023	J	`jnl`	Deep Reinforcement Learning from Hierarchical Weak Preference Feedback. CoRR Alexander Bukharin, Yixiao Li, Pengcheng He, Weizhu Chen, Tuo Zhao
2023	A*	`conf`	Effective Minkowski Dimension of Deep Nonparametric Regression: Function Approximation and Statistical Theories. ICML Zixuan Zhang, Minshuo Chen, Mengdi Wang, Wenjing Liao, Tuo Zhao
2023	J	`jnl`	Effective Minkowski Dimension of Deep Nonparametric Regression: Function Approximation and Statistical Theories. CoRR Zixuan Zhang, Minshuo Chen, Mengdi Wang, Wenjing Liao, Tuo Zhao
2023	—	`conf`	Efficient Long-Range Transformers: You Need to Attend More, but Not Necessarily at Every Layer. EMNLP (Findings) Qingru Zhang, Dhananjay Ram, Cole Hawkins, Sheng Zha, Tuo Zhao
2023	J	`jnl`	Efficient Long-Range Transformers: You Need to Attend More, but Not Necessarily at Every Layer. CoRR Qingru Zhang, Dhananjay Ram, Cole Hawkins, Sheng Zha, Tuo Zhao
2023	J	`jnl`	Good regularity creates large learning rate implicit biases: edge of stability, balancing, and catapult. CoRR Yuqing Wang, Zhenghao Xu, Tuo Zhao, Molei Tao
2023	—	`conf`	HadSkip: Homotopic and Adaptive Layer Skipping of Pre-trained Language Models for Efficient Inference. EMNLP (Findings) Haoyu Wang, Yaqing Wang, Tianci Liu, Tuo Zhao, Jing Gao
2023	A*	`conf`	HomoDistil: Homotopic Task-Agnostic Distillation of Pre-trained Transformers. ICLR Chen Liang, Haoming Jiang, Zheng Li, Xianfeng Tang, Bing Yin, Tuo Zhao
2023	J	`jnl`	HomoDistil: Homotopic Task-Agnostic Distillation of Pre-trained Transformers. CoRR Chen Liang, Haoming Jiang, Zheng Li, Xianfeng Tang, Bin Yin, Tuo Zhao
2023	Misc	`conf`	Joint Estimation of DOA and Distance in Noisy Reverberant Conditions. ICASSP Suliang Bu, Tuo Zhao, Yunxin Zhao
2023	A*	`conf`	Less is More: Task-aware Layer-wise Distillation for Language Model Compression. ICML Chen Liang, Simiao Zuo, Qingru Zhang, Pengcheng He, Weizhu Chen, Tuo Zhao
2023	A*	`conf`	LightToken: A Task and Model-agnostic Lightweight Token Embedding Framework for Pre-trained Language Models. KDD Haoyu Wang, Ruirui Li, Haoming Jiang, Zhengyang Wang, Xianfeng Tang, Bin Bi, Monica Xiao Cheng, Bing Yin, Yaqing Wang, Tuo Zhao, Jing Gao
2023	A*	`conf`	LoSparse: Structured Compression of Large Language Models based on Low-Rank and Sparse Approximation. ICML Yixiao Li, Yifan Yu, Qingru Zhang, Chen Liang, Pengcheng He, Weizhu Chen, Tuo Zhao
2023	J	`jnl`	LoSparse: Structured Compression of Large Language Models based on Low-Rank and Sparse Approximation. CoRR Yixiao Li, Yifan Yu, Qingru Zhang, Chen Liang, Pengcheng He, Weizhu Chen, Tuo Zhao
2023	J	`jnl`	LoftQ: LoRA-Fine-Tuning-Aware Quantization for Large Language Models. CoRR Yixiao Li, Yifan Yu, Chen Liang, Pengcheng He, Nikos Karampatziakis, Weizhu Chen, Tuo Zhao
2023	A*	`conf`	Machine Learning Force Fields with Data Cost Aware Training. ICML Alexander Bukharin, Tianyi Liu, Shengjie Wang, Simiao Zuo, Weihao Gao, Wen Yan, Tuo Zhao
2023	J	`jnl`	Machine Learning Force Fields with Data Cost Aware Training. CoRR Alexander Bukharin, Tianyi Liu, Shengjie Wang, Simiao Zuo, Weihao Gao, Wen Yan, Tuo Zhao
2023	A*	`conf`	Model-Based Reparameterization Policy Gradient Methods: Theory and Practical Algorithms. NeurIPS Shenao Zhang, Boyi Liu, Zhaoran Wang, Tuo Zhao
2023	J	`jnl`	Model-Based Reparameterization Policy Gradient Methods: Theory and Practical Algorithms. CoRR Shenao Zhang, Boyi Liu, Zhaoran Wang, Tuo Zhao
2023	A*	`conf`	Module-wise Adaptive Distillation for Multimodality Foundation Models. NeurIPS Chen Liang, Jiahui Yu, Ming-Hsuan Yang, Matthew Brown, Yin Cui, Tuo Zhao, Boqing Gong, Tianyi Zhou
2023	J	`jnl`	Module-wise Adaptive Distillation for Multimodality Foundation Models. CoRR Chen Liang, Jiahui Yu, Ming-Hsuan Yang, Matthew Brown, Yin Cui, Tuo Zhao, Boqing Gong, Tianyi Zhou
2023	J	`jnl`	Nonparametric Classification on Low Dimensional Manifolds using Overparameterized Convolutional Residual Networks. CoRR Kaiqi Zhang, Zixuan Zhang, Minshuo Chen, Mengdi Wang, Tuo Zhao, Yu-Xiang Wang
2023	J	`jnl`	On Deep Generative Models for Approximation and Estimation of Distributions on Manifolds. CoRR Biraj Dahal, Alexander Havrilla, Minshuo Chen, Tuo Zhao, Wenjing Liao
2023	J	`jnl`	Pivotal Estimation of Linear Discriminant Analysis in High Dimensions. J. Mach. Learn. Res. Ethan X. Fang, Yajun Mei, Yuyang Shi, Qunzhi Xu, Tuo Zhao
2023	J	`jnl`	Provable Benefits of Policy Learning from Human Preferences in Contextual Bandit Problems. CoRR Xiang Ji, Huazheng Wang, Minshuo Chen, Tuo Zhao, Mengdi Wang
2023	A	`conf`	Reinforcement Learning for Adaptive Mesh Refinement. AISTATS Jiachen Yang, Tarik Dzanic, Brenden K. Petersen, Jun Kudo, Ketan Mittal, Vladimir Z. Tomov, Jean-Sylvain Camier, Tuo Zhao, Hongyuan Zha, Tzanio V. Kolev, Robert W. Anderson, Daniel M. Faissol
2023	A*	`conf`	Robust Multi-Agent Reinforcement Learning via Adversarial Regularization: Theoretical Foundation and Stable Algorithms. NeurIPS Alexander Bukharin, Yan Li, Yue Yu, Qingru Zhang, Zhehui Chen, Simiao Zuo, Chao Zhang, Songan Zhang, Tuo Zhao
2023	J	`jnl`	Robust Multi-Agent Reinforcement Learning via Adversarial Regularization: Theoretical Foundation and Stable Algorithms. CoRR Alexander Bukharin, Yan Li, Yue Yu, Qingru Zhang, Zhehui Chen, Simiao Zuo, Chao Zhang, Songan Zhang, Tuo Zhao
2023	A*	`conf`	SMURF-THP: Score Matching-based UnceRtainty quantiFication for Transformer Hawkes Process. ICML Zichong Li, Yanbo Xu, Simiao Zuo, Haoming Jiang, Chao Zhang, Tuo Zhao, Hongyuan Zha
2023	J	`jnl`	SMURF-THP: Score Matching-based UnceRtainty quantiFication for Transformer Hawkes Process. CoRR Zichong Li, Yanbo Xu, Simiao Zuo, Haoming Jiang, Chao Zhang, Tuo Zhao, Hongyuan Zha
2023	J	`jnl`	Sample Complexity of Neural Policy Mirror Descent for Policy Optimization on Low-Dimensional Manifolds. CoRR Zhenghao Xu, Xiang Ji, Minshuo Chen, Mengdi Wang, Tuo Zhao
2023	A*	`conf`	Sample Complexity of Nonparametric Off-Policy Evaluation on Low-Dimensional Manifolds using Deep Networks. ICLR Xiang Ji, Minshuo Chen, Mengdi Wang, Tuo Zhao
2023	A*	`conf`	Score Approximation, Estimation and Distribution Recovery of Diffusion Models on Low-Dimensional Data. ICML Minshuo Chen, Kaixuan Huang, Tuo Zhao, Mengdi Wang
2023	J	`jnl`	Score Approximation, Estimation and Distribution Recovery of Diffusion Models on Low-Dimensional Data. CoRR Minshuo Chen, Kaixuan Huang, Tuo Zhao, Mengdi Wang
2023	J	`jnl`	Score Matching-based Pseudolikelihood Estimation of Neural Marked Spatio-Temporal Point Process with Uncertainty Quantification. CoRR Zichong Li, Qunzhi Xu, Zhenghao Xu, Yajun Mei, Tuo Zhao, Hongyuan Zha
2023	J	`jnl`	Tell Your Model Where to Attend: Post-hoc Attention Steering for LLMs. CoRR Qingru Zhang, Chandan Singh, Liyuan Liu, Xiaodong Liu, Bin Yu, Jianfeng Gao, Tuo Zhao
2022	J	`jnl`	A Manifold Two-Sample Test Study: Integral Probability Metric with Neural Networks. CoRR Jie Wang, Minshuo Chen, Tuo Zhao, Wenjing Liao, Yao Xie
2022	A	`conf`	Adaptive Incentive Design with Multi-Agent Meta-Gradient Reinforcement Learning. AAMAS Jiachen Yang, Ethan Wang, Rakshit S. Trivedi, Tuo Zhao, Hongyuan Zha
2022	—	`conf`	Adversarially Regularized Policy Learning Guided by Trajectory Optimization. L4DC Zhigen Zhao, Simiao Zuo, Tuo Zhao, Ye Zhao
2022	A*	`conf`	Benefits of Overparameterized Convolutional Residual Networks: Function Approximation under Smoothness Constraint. ICML Hao Liu, Minshuo Chen, Siawpeng Er, Wenjing Liao, Tong Zhang, Tuo Zhao
2022	J	`jnl`	Benefits of Overparameterized Convolutional Residual Networks: Function Approximation under Smoothness Constraint. CoRR Hao Liu, Minshuo Chen, Siawpeng Er, Wenjing Liao, Tong Zhang, Tuo Zhao
2022	J	`jnl`	Block Policy Mirror Descent. CoRR Guanghui Lan, Yan Li, Tuo Zhao
2022	—	`conf`	CAMERO: Consistency Regularized Ensemble of Perturbed Language Models with Weight Sharing. ACL (1) Chen Liang, Pengcheng He, Yelong Shen, Weizhu Chen, Tuo Zhao
2022	J	`jnl`	CAMERO: Consistency Regularized Ensemble of Perturbed Language Models with Weight Sharing. CoRR Chen Liang, Pengcheng He, Yelong Shen, Weizhu Chen, Tuo Zhao
2022	—	`conf`	CERES: Pretraining of Graph-Conditioned Transformer for Semi-Structured Session Data. NAACL-HLT Rui Feng, Chen Luo, Qingyu Yin, Bing Yin, Tuo Zhao, Chao Zhang
2022	J	`jnl`	CERES: Pretraining of Graph-Conditioned Transformer for Semi-Structured Session Data. CoRR Rui Feng, Chen Luo, Qingyu Yin, Bing Yin, Tuo Zhao, Chao Zhang
2022	J	`jnl`	Context-Aware Query Rewriting for Improving Users' Search Experience on E-commerce Websites. CoRR Simiao Zuo, Qingyu Yin, Haoming Jiang, Shaohui Xi, Bing Yin, Chao Zhang, Tuo Zhao
2022	J	`jnl`	Deep Learning Assisted End-to-End Synthesis of mm-Wave Passive Networks with 3D EM Structures: A Study on A Transformer-Based Matching Network. CoRR Siawpeng Er, Edward Liu, Minshuo Chen, Yan Li, Yuqi Liu, Tuo Zhao, Hua Wang
2022	J	`jnl`	Deep Nonparametric Estimation of Operators between Infinite Dimensional Spaces. CoRR Hao Liu, Haizhao Yang, Minshuo Chen, Tuo Zhao, Wenjing Liao
2022	J	`jnl`	DiP-GNN: Discriminative Pre-Training of Graph Neural Networks. CoRR Simiao Zuo, Haoming Jiang, Qingyu Yin, Xianfeng Tang, Bing Yin, Tuo Zhao
2022	J	`jnl`	Differentially Private Estimation of Hawkes Process. CoRR Simiao Zuo, Tianyi Liu, Tuo Zhao, Hongyuan Zha
2022	J	`jnl`	Efficient Long Sequence Modeling via State Space Augmented Transformer. CoRR Simiao Zuo, Xiaodong Liu, Jian Jiao, Denis Charles, Eren Manavoglu, Tuo Zhao, Jianfeng Gao
2022	J	`jnl`	First-order Policy Optimization for Robust Markov Decision Process. CoRR Yan Li, Tuo Zhao, Guanghui Lan
2022	A*	`conf`	Frequency-aware SGD for Efficient Embedding Learning with Provable Benefits. ICLR Yan Li, Dhruv Choudhary, Xiaohan Wei, Baichuan Yuan, Bhargav Bhushanam, Tuo Zhao, Guanghui Lan
2022	J	`jnl`	High Dimensional Binary Classification under Label Shift: Phase Transition and Regularization. CoRR Jiahui Cheng, Minshuo Chen, Hao Liu, Tuo Zhao, Wenjing Liao
2022	J	`jnl`	Homotopic Policy Mirror Descent: Policy Convergence, Implicit Regularization, and Improved Sample Complexity. CoRR Yan Li, Tuo Zhao, Guanghui Lan
2022	A*	`conf`	Large Learning Rate Tames Homogeneity: Convergence and Balancing Effect. ICLR Yuqing Wang, Minshuo Chen, Tuo Zhao, Molei Tao
2022	J	`jnl`	Less is More: Task-aware Layer-wise Distillation for Language Model Compression. CoRR Chen Liang, Simiao Zuo, Qingru Zhang, Pengcheng He, Weizhu Chen, Tuo Zhao
2022	—	`conf`	MoEBERT: from BERT to Mixture-of-Experts via Importance-Guided Adaptation. NAACL-HLT Simiao Zuo, Qingru Zhang, Chen Liang, Pengcheng He, Tuo Zhao, Weizhu Chen
2022	J	`jnl`	MoEBERT: from BERT to Mixture-of-Experts via Importance-Guided Adaptation. CoRR Simiao Zuo, Qingru Zhang, Chen Liang, Pengcheng He, Tuo Zhao, Weizhu Chen
2022	J	`jnl`	Modeling Speech Structure to Improve T-F Masks for Speech Enhancement and Recognition. IEEE ACM Trans. Audio Speech Lang. Process. Suliang Bu, Yunxin Zhao, Tuo Zhao, Shaojun Wang, Mei Han
2022	A*	`conf`	No Parameters Left Behind: Sensitivity Guided Adaptive Learning Rate for Training Large Transformer Models. ICLR Chen Liang, Haoming Jiang, Simiao Zuo, Pengcheng He, Xiaodong Liu, Jianfeng Gao, Weizhu Chen, Tuo Zhao
2022	J	`jnl`	No Parameters Left Behind: Sensitivity Guided Adaptive Learning Rate for Training Large Transformer Models. CoRR Chen Liang, Haoming Jiang, Simiao Zuo, Pengcheng He, Xiaodong Liu, Jianfeng Gao, Weizhu Chen, Tuo Zhao
2022	A	`conf`	Noise Regularizes Over-parameterized Rank One Matrix Recovery, Provably. AISTATS Tianyi Liu, Yan Li, Enlu Zhou, Tuo Zhao
2022	J	`jnl`	Noise Regularizes Over-parameterized Rank One Matrix Recovery, Provably. CoRR Tianyi Liu, Yan Li, Enlu Zhou, Tuo Zhao
2022	A*	`conf`	On Deep Generative Models for Approximation and Estimation of Distributions on Manifolds. NeurIPS Biraj Dahal, Alexander Havrilla, Minshuo Chen, Tuo Zhao, Wenjing Liao
2022	A*	`conf`	PLATON: Pruning Large Transformer Models with Upper Confidence Bound of Weight Importance. ICML Qingru Zhang, Simiao Zuo, Chen Liang, Alexander Bukharin, Pengcheng He, Weizhu Chen, Tuo Zhao
2022	J	`jnl`	PLATON: Pruning Large Transformer Models with Upper Confidence Bound of Weight Importance. CoRR Qingru Zhang, Simiao Zuo, Chen Liang, Alexander Bukharin, Pengcheng He, Weizhu Chen, Tuo Zhao
2022	J	`jnl`	Sample Complexity of Nonparametric Off-Policy Evaluation on Low-Dimensional Manifolds using Deep Networks. CoRR Xiang Ji, Minshuo Chen, Mengdi Wang, Tuo Zhao
2022	—	`conf`	Self-Training with Differentiable Teacher. NAACL-HLT (Findings) Simiao Zuo, Yue Yu, Chen Liang, Haoming Jiang, Siawpeng Er, Chao Zhang, Tuo Zhao, Hongyuan Zha
2022	A	`conf`	Steering vector correction in MVDR beamformer for speech enhancement. INTERSPEECH Suliang Bu, Yunxin Zhao, Tuo Zhao
2022	—	`conf`	TDOA Estimation of Speech Source in Noisy Reverberant Environments. SLT Suliang Bu, Tuo Zhao, Yunxin Zhao
2022	A*	`conf`	Taming Sparsely Activated Transformer with Stochastic Experts. ICLR Simiao Zuo, Xiaodong Liu, Jian Jiao, Young Jin Kim, Hany Hassan, Ruofei Zhang, Jianfeng Gao, Tuo Zhao
2022	J	`jnl`	Understanding users' trust transfer mechanism in a blockchain-enabled platform: A mixed methods study. Decis. Support Syst. Zhen Shao, Lin Zhang, Susan A. Brown, Tuo Zhao
2021	A*	`conf`	A Hypergradient Approach to Robust Regression without Correspondence. ICLR Yujia Xie, Yixiu Mao, Simiao Zuo, Hongteng Xu, Xiaojing Ye, Tuo Zhao, Hongyuan Zha
2021	—	`conf`	ARCH: Efficient Adversarial Regularized Training with Caching. EMNLP (Findings) Simiao Zuo, Chen Liang, Haoming Jiang, Pengcheng He, Xiaodong Liu, Jianfeng Gao, Weizhu Chen, Tuo Zhao
2021	J	`jnl`	ARCH: Efficient Adversarial Regularized Training with Caching. CoRR Simiao Zuo, Chen Liang, Haoming Jiang, Pengcheng He, Xiaodong Liu, Jianfeng Gao, Weizhu Chen, Tuo Zhao
2021	J	`jnl`	Adaptive Incentive Design with Multi-Agent Meta-Gradient Reinforcement Learning. CoRR Jiachen Yang, Ethan Wang, Rakshit S. Trivedi, Tuo Zhao, Hongyuan Zha
2021	—	`conf`	Adversarial Regularization as Stackelberg Game: An Unrolled Optimization Approach. EMNLP (1) Simiao Zuo, Chen Liang, Haoming Jiang, Xiaodong Liu, Pengcheng He, Jianfeng Gao, Weizhu Chen, Tuo Zhao
2021	J	`jnl`	Adversarial Training as Stackelberg Game: An Unrolled Optimization Approach. CoRR Simiao Zuo, Chen Liang, Haoming Jiang, Xiaodong Liu, Pengcheng He, Jianfeng Gao, Weizhu Chen, Tuo Zhao
2021	J	`jnl`	Adversarially Regularized Policy Learning Guided by Trajectory Optimization. CoRR Zhigen Zhao, Simiao Zuo, Tuo Zhao, Ye Zhao
2021	A*	`conf`	Besov Function Approximation and Binary Classification on Low-Dimensional Manifolds Using Convolutional Residual Networks. ICML Hao Liu, Minshuo Chen, Tuo Zhao, Wenjing Liao
2021	J	`jnl`	Besov Function Approximation and Binary Classification on Low-Dimensional Manifolds Using Convolutional Residual Networks. CoRR Hao Liu, Minshuo Chen, Tuo Zhao, Wenjing Liao
2021	J	`jnl`	COUnty aggRegation mixup AuGmEntation (COURAGE) COVID-19 Prediction. CoRR Siawpeng Er, Shihao Yang, Tuo Zhao
2021	—	`conf`	Fine-Tuning Pre-trained Language Model with Weak Supervision: A Contrastive-Regularized Self-Training Approach. NAACL-HLT Yue Yu, Simiao Zuo, Haoming Jiang, Wendi Ren, Tuo Zhao, Chao Zhang
2021	J	`jnl`	Frequency-aware SGD for Efficient Embedding Learning with Provable Benefits. CoRR Yan Li, Dhruv Choudhary, Xiaohan Wei, Baichuan Yuan, Bhargav Bhushanam, Tuo Zhao, Guanghui Lan
2021	A*	`conf`	How Important is the Train-Validation Split in Meta-Learning? ICML Yu Bai, Minshuo Chen, Pan Zhou, Tuo Zhao, Jason D. Lee, Sham M. Kakade, Huan Wang, Caiming Xiong
2021	J	`jnl`	Implicit Regularization of Bregman Proximal Point Algorithm and Mirror Descent on Separable Data. CoRR Yan Li, Caleb Ju, Ethan X. Fang, Tuo Zhao
2021	J	`jnl`	Large Learning Rate Tames Homogeneity: Convergence and Balancing Effect. CoRR Yuqing Wang, Minshuo Chen, Tuo Zhao, Molei Tao
2021	J	`jnl`	Learning Generalizable Vision-Tactile Robotic Grasping Strategy for Deformable Objects via Transformer. CoRR Yunhai Han, Rahul Batra, Nathan Boyd, Tuo Zhao, Yu She, Seth Hutchinson, Ye Zhao
2021	A	`conf`	Learning to Defend by Learning to Attack. AISTATS Haoming Jiang, Zhehui Chen, Yuyang Shi, Bo Dai, Tuo Zhao
2021	—	`conf`	Named Entity Recognition with Small Strongly Labeled and Large Weakly Labeled Data. ACL/IJCNLP (1) Haoming Jiang, Danqing Zhang, Tianyu Cao, Bing Yin, Tuo Zhao
2021	J	`jnl`	Named Entity Recognition with Small Strongly Labeled and Large Weakly Labeled Data. CoRR Haoming Jiang, Danqing Zhang, Tianyu Cao, Bing Yin, Tuo Zhao
2021	A	`conf`	Noisy Gradient Descent Converges to Flat Minima for Nonconvex Matrix Factorization. AISTATS Tianyi Liu, Yan Li, Song Wei, Enlu Zhou, Tuo Zhao
2021	J	`jnl`	Noisy Gradient Descent Converges to Flat Minima for Nonconvex Matrix Factorization. CoRR Tianyi Liu, Yan Li, Song Wei, Enlu Zhou, Tuo Zhao
2021	J	`jnl`	Permutation Invariant Policy Optimization for Mean-Field Multi-Agent Reinforcement Learning: A Principled Approach. CoRR Yan Li, Lingxiao Wang, Jiachen Yang, Ethan Wang, Zhaoran Wang, Tuo Zhao, Hongyuan Zha
2021	A*	`conf`	Pessimism Meets Invariance: Provably Efficient Offline Mean-Field Multi-Agent RL. NeurIPS Minshuo Chen, Yan Li, Ethan Wang, Zhuoran Yang, Zhaoran Wang, Tuo Zhao
2021	A	`conf`	QUEACO: Borrowing Treasures from Weakly-labeled Behavior Data for Query Attribute Value Extraction. CIKM Danqing Zhang, Zheng Li, Tianyu Cao, Chen Luo, Tony Wu, Hanqing Lu, Yiwei Song, Bing Yin, Tuo Zhao, Qiang Yang
2021	J	`jnl`	QUEACO: Borrowing Treasures from Weakly-labeled Behavior Data for Query Attribute Value Extraction. CoRR Danqing Zhang, Zheng Li, Tianyu Cao, Chen Luo, Tony Wu, Hanqing Lu, Yiwei Song, Bing Yin, Tuo Zhao, Qiang Yang
2021	J	`jnl`	Reinforcement Learning for Adaptive Mesh Refinement. CoRR Jiachen Yang, Tarik Dzanic, Brenden K. Petersen, Jun Kudo, Ketan Mittal, Vladimir Z. Tomov, Jean-Sylvain Camier, Tuo Zhao, Hongyuan Zha, Tzanio V. Kolev, Robert W. Anderson, Daniel M. Faissol
2021	J	`jnl`	Self-Training with Differentiable Teacher. CoRR Simiao Zuo, Yue Yu, Chen Liang, Haoming Jiang, Siawpeng Er, Chao Zhang, Tuo Zhao, Hongyuan Zha
2021	J	`jnl`	Spectrum Truncation Power Iteration for Agnostic Matrix Phase Retrieval. IEEE Trans. Signal Process. Lewis Liu, Songtao Lu, Tuo Zhao, Zhaoran Wang
2021	—	`conf`	Super Tickets in Pre-Trained Language Models: From Model Compression to Improving Generalization. ACL/IJCNLP (1) Chen Liang, Simiao Zuo, Minshuo Chen, Haoming Jiang, Xiaodong Liu, Pengcheng He, Tuo Zhao, Weizhu Chen
2021	J	`jnl`	Super Tickets in Pre-Trained Language Models: From Model Compression to Improving Generalization. CoRR Chen Liang, Simiao Zuo, Minshuo Chen, Haoming Jiang, Xiaodong Liu, Pengcheng He, Tuo Zhao, Weizhu Chen
2021	J	`jnl`	Taming Sparsely Activated Transformer with Stochastic Experts. CoRR Simiao Zuo, Xiaodong Liu, Jian Jiao, Young Jin Kim, Hany Hassan, Ruofei Zhang, Tuo Zhao, Jianfeng Gao
2021	—	`conf`	Token-wise Curriculum Learning for Neural Machine Translation. EMNLP (Findings) Chen Liang, Haoming Jiang, Xiaodong Liu, Pengcheng He, Weizhu Chen, Jianfeng Gao, Tuo Zhao
2021	J	`jnl`	Token-wise Curriculum Learning for Neural Machine Translation. CoRR Chen Liang, Haoming Jiang, Xiaodong Liu, Pengcheng He, Weizhu Chen, Jianfeng Gao, Tuo Zhao
2021	—	`conf`	Towards Automatic Evaluation of Dialog Systems: A Model-Free Off-Policy Evaluation Approach. EMNLP (1) Haoming Jiang, Bo Dai, Mengjiao Yang, Tuo Zhao, Wei Wei
2021	J	`jnl`	Towards Automatic Evaluation of Dialog Systems: A Model-Free Off-Policy Evaluation Approach. CoRR Haoming Jiang, Bo Dai, Mengjiao Yang, Wei Wei, Tuo Zhao
2021	—	`conf`	UNet++-Based Multi-Channel Speech Dereverberation and Distant Speech Recognition. ISCSLP Tuo Zhao, Yunxin Zhao, Shaojun Wang, Mei Han
2020	J	`jnl`	A Hypergradient Approach to Robust Regression without Correspondence. CoRR Yujia Xie, Yixiu Mao, Simiao Zuo, Hongteng Xu, Xiaojing Ye, Tuo Zhao, Hongyuan Zha
2020	A*	`conf`	BOND: BERT-Assisted Open-Domain Named Entity Recognition with Distant Supervision. KDD Chen Liang, Yue Yu, Haoming Jiang, Siawpeng Er, Ruijia Wang, Tuo Zhao, Chao Zhang
2020	J	`jnl`	BOND: BERT-Assisted Open-Domain Named Entity Recognition with Distant Supervision. CoRR Chen Liang, Yue Yu, Haoming Jiang, Siawpeng Er, Ruijia Wang, Tuo Zhao, Chao Zhang
2020	—	`conf`	Calibrated Language Model Fine-Tuning for In- and Out-of-Distribution Data. EMNLP (1) Lingkai Kong, Haoming Jiang, Yuchen Zhuang, Jie Lyu, Tuo Zhao, Chao Zhang
2020	J	`jnl`	Calibrated Language Model Fine-Tuning for In- and Out-of-Distribution Data. CoRR Lingkai Kong, Haoming Jiang, Yuchen Zhuang, Jie Lyu, Tuo Zhao, Chao Zhang
2020	A*	`conf`	Deep Reinforcement Learning with Robust and Smooth Policy. ICML Qianli Shen, Yan Li, Haoming Jiang, Zhaoran Wang, Tuo Zhao
2020	J	`jnl`	Deep Reinforcement Learning with Smooth Policy. CoRR Qianli Shen, Yan Li, Haoming Jiang, Zhaoran Wang, Tuo Zhao
2020	J	`jnl`	Differentiable Top-k Operator with Optimal Transport. CoRR Yujia Xie, Hanjun Dai, Minshuo Chen, Bo Dai, Tuo Zhao, Hongyuan Zha, Wei Wei, Tomas Pfister
2020	A*	`conf`	Differentiable Top-k with Optimal Transport. NeurIPS Yujia Xie, Hanjun Dai, Minshuo Chen, Bo Dai, Tuo Zhao, Hongyuan Zha, Wei Wei, Tomas Pfister
2020	J	`jnl`	Doubly Robust Off-Policy Learning on Low-Dimensional Manifolds by Deep Neural Networks. CoRR Minshuo Chen, Hao Liu, Wenjing Liao, Tuo Zhao
2020	J	`jnl`	Fine-Tuning Pre-trained Language Model with Weak Supervision: A Contrastive-Regularized Self-Training Approach. CoRR Yue Yu, Simiao Zuo, Haoming Jiang, Wendi Ren, Tuo Zhao, Chao Zhang
2020	J	`jnl`	How Important is the Train-Validation Split in Meta-Learning? CoRR Yu Bai, Minshuo Chen, Pan Zhou, Tuo Zhao, Jason D. Lee, Sham M. Kakade, Huan Wang, Caiming Xiong
2020	A*	`conf`	Implicit Bias of Gradient Descent based Adversarial Training on Separable Data. ICLR Yan Li, Ethan X. Fang, Huan Xu, Tuo Zhao
2020	A*	`conf`	Multi-Domain Neural Machine Translation with Word-Level Adaptive Layer-wise Domain Mixing. ACL Haoming Jiang, Chen Liang, Chong Wang, Tuo Zhao
2020	A*	`conf`	On Computation and Generalization of Generative Adversarial Imitation Learning. ICLR Minshuo Chen, Yizhou Wang, Tianyi Liu, Zhuoran Yang, Xingguo Li, Zhaoran Wang, Tuo Zhao
2020	J	`jnl`	On Computation and Generalization of Generative Adversarial Imitation Learning. CoRR Minshuo Chen, Yizhou Wang, Tianyi Liu, Zhuoran Yang, Xingguo Li, Zhaoran Wang, Tuo Zhao
2020	A	`conf`	On Generalization Bounds of a Family of Recurrent Neural Networks. AISTATS Minshuo Chen, Xingguo Li, Tuo Zhao
2020	J	`jnl`	Picasso: A Sparse Learning Library for High Dimensional Data Analysis in R and Python. CoRR Jason Ge, Xingguo Li, Haoming Jiang, Han Liu, Tong Zhang, Mengdi Wang, Tuo Zhao
2020	J	`jnl`	Residual Network Based Direct Synthesis of EM Structures: A Study on One-to-One Transformers. CoRR David Joseph Munzer, Siawpeng Er, Minshuo Chen, Yan Li, Naga Sasikanth Mannem, Tuo Zhao, Hua Wang
2020	A*	`conf`	SMART: Robust and Efficient Fine-Tuning for Pre-trained Natural Language Models through Principled Regularized Optimization. ACL Haoming Jiang, Pengcheng He, Weizhu Chen, Xiaodong Liu, Jianfeng Gao, Tuo Zhao
2020	J	`jnl`	Spatial Resolution Enhancement of Remote Sensing Hyperspectral Images With Localized Spatial-Spectral Dictionary Pair. IEEE Access Yifan Zhang, Jin Tian, Tuo Zhao, Shaohui Mei
2020	J	`jnl`	Statistical Guarantees of Generative Adversarial Networks for Distribution Estimation. CoRR Minshuo Chen, Wenjing Liao, Hongyuan Zha, Tuo Zhao
2020	—	`conf`	The Role of Mobile Social Application in Stimulating Learning Stickiness in Blended Learning. PACIS Lin Zhang, Zhen Shao, Tuo Zhao, Susan A. Brown
2020	J	`jnl`	The flare Package for High Dimensional Linear Regression and Precision Matrix Estimation in R. CoRR Xingguo Li, Tuo Zhao, Xiaoming Yuan, Han Liu
2020	J	`jnl`	The huge Package for High-dimensional Undirected Graph Estimation in R. CoRR Tuo Zhao, Han Liu, Kathryn Roeder, John Lafferty, Larry A. Wasserman
2020	A*	`conf`	Towards Understanding Hierarchical Learning: Benefits of Neural Representations. NeurIPS Minshuo Chen, Yu Bai, Jason D. Lee, Tuo Zhao, Huan Wang, Caiming Xiong, Richard Socher
2020	J	`jnl`	Towards Understanding Hierarchical Learning: Benefits of Neural Representations. CoRR Minshuo Chen, Yu Bai, Jason D. Lee, Tuo Zhao, Huan Wang, Caiming Xiong, Richard Socher
2020	A*	`conf`	Transformer Hawkes Process. ICML Simiao Zuo, Haoming Jiang, Zichong Li, Tuo Zhao, Hongyuan Zha
2020	J	`jnl`	Transformer Hawkes Process. CoRR Simiao Zuo, Haoming Jiang, Zichong Li, Tuo Zhao, Hongyuan Zha
2020	A*	`conf`	Why Do Deep Residual Networks Generalize Better than Deep Feedforward Networks? - A Neural Tangent Kernel Perspective. NeurIPS Kaixuan Huang, Yuqing Wang, Molei Tao, Tuo Zhao
2020	J	`jnl`	Why Do Deep Residual Networks Generalize Better than Deep Feedforward Networks? - A Neural Tangent Kernel Perspective. CoRR Kaixuan Huang, Yuqing Wang, Molei Tao, Tuo Zhao
2019	A*	`conf`	Efficient Approximation of Deep ReLU Networks for Functions on Low Dimensional Manifolds. NeurIPS Minshuo Chen, Haoming Jiang, Wenjing Liao, Tuo Zhao
2019	J	`jnl`	Efficient Approximation of Deep ReLU Networks for Functions on Low Dimensional Manifolds. CoRR Minshuo Chen, Haoming Jiang, Wenjing Liao, Tuo Zhao
2019	J	`jnl`	Inductive Bias of Gradient Descent based Adversarial Training on Separable Data. CoRR Yan Li, Ethan X. Fang, Huan Xu, Tuo Zhao
2019	—	`conf`	Learning to Defense by Learning to Attack. DGS@ICLR Zhehui Chen, Haoming Jiang, Yuyang Shi, Bo Dai, Tuo Zhao
2019	A*	`conf`	Meta Learning with Relational Information for Short Sequences. NeurIPS Yujia Xie, Haoming Jiang, Feng Liu, Tuo Zhao, Hongyuan Zha
2019	J	`jnl`	Meta Learning with Relational Information for Short Sequences. CoRR Yujia Xie, Haoming Jiang, Feng Liu, Tuo Zhao, Hongyuan Zha
2019	J	`jnl`	Misspecified nonconvex statistical optimization for sparse phase retrieval. Math. Program. Zhuoran Yang, Lin F. Yang, Ethan X. Fang, Tuo Zhao, Zhaoran Wang, Matey Neykov
2019	J	`jnl`	Multi-Domain Neural Machine Translation with Word-Level Adaptive Layer-wise Domain Mixing. CoRR Haoming Jiang, Chen Liang, Chong Wang, Tuo Zhao
2019	—	`conf`	On Computation and Generalization of Generative Adversarial Networks under Spectrum Control. ICLR (Poster) Haoming Jiang, Zhehui Chen, Minshuo Chen, Feng Liu, Dingding Wang, Tuo Zhao
2019	A	`conf`	On Constrained Nonconvex Stochastic Optimization: A Case Study for Generalized Eigenvalue Decomposition. AISTATS Zhehui Chen, Xingguo Li, Lin Yang, Jarvis D. Haupt, Tuo Zhao
2019	A	`conf`	On Fast Convergence of Proximal Algorithms for SQRT-Lasso Optimization: Don't Worry About its Nonsmooth Loss Function. UAI Xingguo Li, Haoming Jiang, Jarvis D. Haupt, Raman Arora, Han Liu, Mingyi Hong, Tuo Zhao
2019	J	`jnl`	On Generalization Bounds of a Family of Recurrent Neural Networks. CoRR Minshuo Chen, Xingguo Li, Tuo Zhao
2019	—	`conf`	On Scalable and Efficient Computation of Large Scale Optimal Transport. DGS@ICLR Yujia Xie, Minshuo Chen, Haoming Jiang, Tuo Zhao, Hongyuan Zha
2019	A*	`conf`	On Scalable and Efficient Computation of Large Scale Optimal Transport. ICML Yujia Xie, Minshuo Chen, Haoming Jiang, Tuo Zhao, Hongyuan Zha
2019	J	`jnl`	On Scalable and Efficient Computation of Large Scale Optimal Transport. CoRR Yujia Xie, Minshuo Chen, Haoming Jiang, Tuo Zhao, Hongyuan Zha
2019	A	`conf`	Online Factorization and Partition of Complex Networks by Random Walk. UAI Lin F. Yang, Zheng Yu, Vladimir Braverman, Tuo Zhao, Mengdi Wang
2019	J	`jnl`	Picasso: A Sparse Learning Library for High Dimensional Data Analysis in R and Python. J. Mach. Learn. Res. Jason Ge, Xingguo Li, Haoming Jiang, Han Liu, Tong Zhang, Mengdi Wang, Tuo Zhao
2019	J	`jnl`	Review wearable sensing system for gait recognition. Clust. Comput. Gelan Yang, Wei Tan, Huixia Jin, Tuo Zhao, Li Tu
2019	J	`jnl`	SMART: Robust and Efficient Fine-Tuning for Pre-trained Natural Language Models through Principled Regularized Optimization. CoRR Haoming Jiang, Pengcheng He, Weizhu Chen, Xiaodong Liu, Jianfeng Gao, Tuo Zhao
2019	J	`jnl`	Symmetry, Saddle Points, and Global Optimization Landscape of Nonconvex Matrix Factorization. IEEE Trans. Inf. Theory Xingguo Li, Junwei Lu, Raman Arora, Jarvis D. Haupt, Han Liu, Zhaoran Wang, Tuo Zhao
2019	A*	`conf`	Toward Understanding the Importance of Noise in Training Neural Networks. ICML Mo Zhou, Tianyi Liu, Yan Li, Dachao Lin, Enlu Zhou, Tuo Zhao
2019	J	`jnl`	Towards Understanding the Importance of Noise in Training Neural Networks. CoRR Mo Zhou, Tianyi Liu, Yan Li, Dachao Lin, Enlu Zhou, Tuo Zhao
2019	A*	`conf`	Towards Understanding the Importance of Shortcut Connections in Residual Networks. NeurIPS Tianyi Liu, Minshuo Chen, Mo Zhou, Simon S. Du, Enlu Zhou, Tuo Zhao
2019	J	`jnl`	Towards Understanding the Importance of Shortcut Connections in Residual Networks. CoRR Tianyi Liu, Minshuo Chen, Mo Zhou, Simon S. Du, Enlu Zhou, Tuo Zhao
2018	J	`jnl`	Detecting Nonlinear Causality in Multivariate Time Series with Sparse Additive Models. CoRR Yingxiang Yang, Adams Wei Yu, Zhaoran Wang, Tuo Zhao
2018	A*	`conf`	Dimensionality Reduction for Stationary Time Series via Stochastic Nonconvex Optimization. NeurIPS Minshuo Chen, Lin Yang, Mengdi Wang, Tuo Zhao
2018	J	`jnl`	Dimensionality Reduction for Stationary Time Series via Stochastic Nonconvex Optimization. CoRR Minshuo Chen, Lin Yang, Mengdi Wang, Tuo Zhao
2018	J	`jnl`	Learning to Defense by Learning to Attack. CoRR Zhehui Chen, Haoming Jiang, Bo Dai, Tuo Zhao
2018	J	`jnl`	On Computation and Generalization of GANs with Spectrum Control. CoRR Haoming Jiang, Zhehui Chen, Minshuo Chen, Feng Liu, Dingding Wang, Tuo Zhao
2018	J	`jnl`	On Landscape of Lagrangian Functions and Stochastic Search for Constrained Nonconvex Optimization. CoRR Zhehui Chen, Xingguo Li, Lin F. Yang, Jarvis D. Haupt, Tuo Zhao
2018	J	`jnl`	On Tighter Generalization Bound for Deep Neural Networks: CNNs, ResNets, and Beyond. CoRR Xingguo Li, Junwei Lu, Zhaoran Wang, Jarvis D. Haupt, Tuo Zhao
2018	A*	`conf`	Provable Gaussian Embedding with One Observation. NeurIPS Ming Yu, Zhuoran Yang, Tuo Zhao, Mladen Kolar, Zhaoran Wang
2018	J	`jnl`	Provable Gaussian Embedding with One Observation. CoRR Ming Yu, Zhuoran Yang, Tuo Zhao, Mladen Kolar, Zhaoran Wang
2018	Misc	`conf`	Symmetry. Saddle Points, and Global Optimization Landscape of Nonconvex Matrix Factorization. ITA Xingguo Li, Jarvis D. Haupt, Junwei Lu, Zhaoran Wang, Raman Arora, Han Liu, Tuo Zhao
2018	A*	`conf`	The Physical Systems Behind Optimization Algorithms. NeurIPS Lin F. Yang, Raman Arora, Vladimir Braverman, Tuo Zhao
2018	J	`jnl`	Toward Deeper Understanding of Nonconvex Stochastic Optimization with Momentum using Diffusion Approximations. CoRR Tianyi Liu, Zhehui Chen, Enlu Zhou, Tuo Zhao
2018	A*	`conf`	Towards Understanding Acceleration Tradeoff between Momentum and Asynchrony in Nonconvex Stochastic Optimization. NeurIPS Tianyi Liu, Shiyang Li, Jianping Shi, Enlu Zhou, Tuo Zhao
2018	J	`jnl`	Towards Understanding Acceleration Tradeoff between Momentum and Asynchrony in Nonconvex Stochastic Optimization. CoRR Tianyi Liu, Shiyang Li, Jianping Shi, Enlu Zhou, Tuo Zhao
2017	J	`jnl`	An enhance excavation equipments classification algorithm based on acoustic spectrum dynamic feature. Multidimens. Syst. Signal Process. Jiuwen Cao, Wuhao Huang, Tuo Zhao, Jianzhong Wang, Ruirong Wang
2017	—	`conf`	Deep Hyperspherical Learning. NIPS Weiyang Liu, Yan-Ming Zhang, Xingguo Li, Zhen Liu, Bo Dai, Tuo Zhao, Le Song
2017	J	`jnl`	Deep Hyperspherical Learning. CoRR Weiyang Liu, Yan-Ming Zhang, Xingguo Li, Zhiding Yu, Bo Dai, Tuo Zhao, Le Song
2017	J	`jnl`	Dynamic Factorization and Partition of Complex Networks. CoRR Lin F. Yang, Vladimir Braverman, Tuo Zhao, Mengdi Wang
2017	J	`jnl`	Excavation equipment classification based on improved MFCC features and ELM. Neurocomputing Jiuwen Cao, Tuo Zhao, Jianzhong Wang, Ruirong Wang, Yun Chen
2017	J	`jnl`	Homotopy Parametric Simplex Method for Sparse Learning. CoRR Haotian Pang, Tuo Zhao, Robert J. Vanderbei, Han Liu
2017	—	`conf`	Hyperspectral and multispectral image fusion using local spatial-spectral dictionary pair. APSIPA Yifan Zhang, Tuo Zhao, Mingyi He
2017	J	`jnl`	Misspecified Nonconvex Statistical Optimization for Phase Retrieval. CoRR Zhuoran Yang, Lin F. Yang, Ethan X. Fang, Tuo Zhao, Zhaoran Wang, Matey Neykov
2017	J	`jnl`	On Faster Convergence of Cyclic Block Coordinate Descent-type Methods for Strongly Convex Minimization. J. Mach. Learn. Res. Xingguo Li, Tuo Zhao, Raman Arora, Han Liu, Mingyi Hong
2017	J	`jnl`	On Quadratic Convergence of DC Proximal Newton Algorithm for Nonconvex Sparse Learning in High Dimensions. CoRR Xingguo Li, Lin F. Yang, Jason Ge, Jarvis D. Haupt, Tong Zhang, Tuo Zhao
2017	—	`conf`	On Quadratic Convergence of DC Proximal Newton Algorithm in Nonconvex Sparse Learning. NIPS Xingguo Li, Lin Yang, Jason Ge, Jarvis D. Haupt, Tong Zhang, Tuo Zhao
2017	J	`jnl`	Online Multiview Representation Learning: Dropping Convexity for Better Efficiency. CoRR Zhehui Chen, Forest L. Yang, Chris Junchi Li, Tuo Zhao
2017	A*	`conf`	Online Partial Least Square Optimization: Dropping Convexity for Better Efficiency and Scalability. ICML Zhehui Chen, Lin F. Yang, Chris Junchi Li, Tuo Zhao
2017	—	`conf`	Parametric Simplex Method for Sparse Learning. NIPS Haotian Pang, Han Liu, Robert J. Vanderbei, Tuo Zhao
2017	A	`conf`	The Opensesame NIST 2016 Speaker Recognition Evaluation System. INTERSPEECH Gang Liu, Qi Qian, Zhibin Wang, Qingen Zhao, Tianzhou Wang, Hao Li, Jian Xue, Shenghuo Zhu, Rong Jin, Tuo Zhao
2016	J	`jnl`	A First Order Free Lunch for SQRT-Lasso. CoRR Xingguo Li, Jarvis D. Haupt, Raman Arora, Han Liu, Mingyi Hong, Tuo Zhao
2016	A	`conf`	An Improved Convergence Analysis of Cyclic Block Coordinate Descent-type Methods for Strongly Convex Minimization. AISTATS Xingguo Li, Tuo Zhao, Raman Arora, Han Liu, Mingyi Hong
2016	J	`jnl`	An Improved Convergence Analysis of Cyclic Block Coordinate Descent-type Methods for Strongly Convex Minimization. CoRR Xingguo Li, Tuo Zhao, Raman Arora, Han Liu, Mingyi Hong
2016	J	`jnl`	Ensemble Acoustic Modeling for CD-DNN-HMM Using Random Forests of Phonetic Decision Trees. J. Signal Process. Syst. Tuo Zhao, Yunxin Zhao, Xin Chen
2016	C	`conf`	Hyperspectral and multispectral image fusion using collaborative representation with local adaptive dictionary pair. IGARSS Tuo Zhao, Yifan Zhang, Xiaoqin Xue, Mingyi He
2016	—	`conf`	NESTT: A Nonconvex Primal-Dual Splitting Method for Distributed and Stochastic Optimization. NIPS Davood Hajinezhad, Mingyi Hong, Tuo Zhao, Zhaoran Wang
2016	J	`jnl`	NESTT: A Nonconvex Primal-Dual Splitting Method for Distributed and Stochastic Optimization. CoRR Davood Hajinezhad, Mingyi Hong, Tuo Zhao, Zhaoran Wang
2016	A*	`conf`	Stochastic Variance Reduced Optimization for Nonconvex Sparse Learning. ICML Xingguo Li, Tuo Zhao, Raman Arora, Han Liu, Jarvis D. Haupt
2016	J	`jnl`	Stochastic Variance Reduced Optimization for Nonconvex Sparse Learning. CoRR Xingguo Li, Tuo Zhao, Raman Arora, Han Liu, Jarvis D. Haupt
2016	C	`conf`	Subpixel mapping of hyperspectral images based on collaborative representation. IGARSS Xiaoqin Xue, Yifan Zhang, Tuo Zhao, Mingyi He
2016	J	`jnl`	Symmetry, Saddle Points, and Global Geometry of Nonconvex Matrix Factorization. CoRR Xingguo Li, Zhaoran Wang, Junwei Lu, Raman Arora, Jarvis D. Haupt, Han Liu, Tuo Zhao
2016	J	`jnl`	The Physical Systems Behind Optimization Algorithms. CoRR Lin F. Yang, Raman Arora, Vladimir Braverman, Tuo Zhao
2015	—	`conf`	A Nonconvex Optimization Framework for Low Rank Matrix Estimation. NIPS Tuo Zhao, Zhaoran Wang, Han Liu
2015	J	`jnl`	Calibrated multivariate regression with application to neural semantic basis discovery. J. Mach. Learn. Res. Han Liu, Lie Wang, Tuo Zhao
2015	J	`jnl`	The flare package for high dimensional linear regression and precision matrix estimation in R. J. Mach. Learn. Res. Xingguo Li, Tuo Zhao, Xiaoming Yuan, Han Liu
2015	A	`conf`	Time-frequency kernel-based CNN for speech recognition. INTERSPEECH Tuo Zhao, Yunxin Zhao, Xin Chen
2014	—	`conf`	Accelerated Mini-batch Randomized Block Coordinate Descent Method. NIPS Tuo Zhao, Mo Yu, Yiming Wang, Raman Arora, Han Liu
2014	—	`conf`	Building an ensemble of CD-DNN-HMM acoustic model using random forests of phonetic decision trees. ISCSLP Tuo Zhao, Yunxin Zhao, Xin Chen
2014	J	`jnl`	Calibrated Precision Matrix Estimation for High-Dimensional Elliptical Distributions. IEEE Trans. Inf. Theory Tuo Zhao, Han Liu
2014	—	`conf`	Multilevel sampling and aggregation for discriminative training. ISCSLP Yunxin Zhao, Tuo Zhao, Xin Chen
2014	—	`conf`	Multivariate Regression with Calibration. NIPS Han Liu, Lie Wang, Tuo Zhao
2014	J	`jnl`	Pathwise Coordinate Optimization for Sparse Learning: Algorithm and Theory. CoRR Tuo Zhao, Han Liu, Tong Zhang
2013	J	`jnl`	CODA: high dimensional copula discriminant analysis. J. Mach. Learn. Res. Fang Han, Tuo Zhao, Han Liu
2013	J	`jnl`	Calibrated Multivariate Regression with Application to Neural Semantic Basis Discovery. CoRR Han Liu, Lie Wang, Tuo Zhao
2013	—	`conf`	Sparse Inverse Covariance Estimation with Calibration. NIPS Tuo Zhao, Han Liu
2012	—	`conf`	Smooth-projected Neighborhood Pursuit for High-dimensional Nonparanormal Graph Estimation. NIPS Tuo Zhao, Kathryn Roeder, Han Liu
2012	A	`conf`	Sparse Additive Machine. AISTATS Tuo Zhao, Han Liu
2012	J	`jnl`	The huge Package for High-dimensional Undirected Graph Estimation in R. J. Mach. Learn. Res. Tuo Zhao, Han Liu, Kathryn Roeder, John D. Lafferty, Larry A. Wasserman
2010	J	`jnl`	Projected gradient method for kernel discriminant nonnegative matrix factorization and the applications. Signal Process. Zhizheng Liang, Youfu Li, Tuo Zhao
2009	J	`jnl`	Predicting RNA secondary structure based on the class information and Hopfield network. Comput. Biol. Medicine Quan Zou, Tuo Zhao, Yang Liu, Maozu Guo
2008	J	`jnl`	Interest filter vs. interest operator: Face recognition using Fisher linear discriminant based on interest filter representation. Pattern Recognit. Lett. Tuo Zhao, Zhizheng Liang, David Zhang, Quan Zou
2007	—	`conf`	A Novel Null Space-Based Kernel Discriminant Analysis for Face Recognition. ICB Tuo Zhao, Zhizheng Liang, David Zhang, Yahui Liu
2006	B	`conf`	Curve Mapping Based Illumination Adjustment for Face Detection. ACIVS Xiaoyue Jiang, Tuo Zhao, Rongchun Zhao
2006	—	`conf`	Feature selection for linear support vector machines. ICPR (2) Zhizheng Liang, Tuo Zhao
2005	C	`conf`	Re-lighting and Compensation for Face Images. CAIP Xiaoyue Jiang, Tuo Zhao, Rong Xiao, Rongchun Zhao