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2020 – today
- 2024
[j26]Hao Liu, Haizhao Yang, Minshuo Chen, Tuo Zhao, Wenjing Liao:
Deep Nonparametric Estimation of Operators between Infinite Dimensional Spaces. J. Mach. Learn. Res. 25: 24:1-24:67 (2024)- [j25]Zhenghao Xu, Xiang Ji, Minshuo Chen, Mengdi Wang, Tuo Zhao:
Sample Complexity of Neural Policy Mirror Descent for Policy Optimization on Low-Dimensional Manifolds. J. Mach. Learn. Res. 25: 226:1-226:67 (2024) - [j24]Yan Li
, Guanghui Lan, Tuo Zhao:
Homotopic policy mirror descent: policy convergence, algorithmic regularization, and improved sample complexity. Math. Program. 207(1): 457-513 (2024) - [j23]Tingting Zhao, Guixi Li, Tuo Zhao, Yarui Chen, Ning Xie, Gang Niu, Masashi Sugiyama:
Learning explainable task-relevant state representation for model-free deep reinforcement learning. Neural Networks 180: 106741 (2024) - [c111]Haoyu Wang, Tianci Liu, Ruirui Li, Monica Xiao Cheng, Tuo Zhao, Jing Gao:
RoseLoRA: Row and Column-wise Sparse Low-rank Adaptation of Pre-trained Language Model for Knowledge Editing and Fine-tuning. EMNLP 2024: 996-1008 - [c110]Haoyu Wang, Ruirui Li, Haoming Jiang, Jinjin Tian, Zhengyang Wang, Chen Luo, Xianfeng Tang, Monica Xiao Cheng, Tuo Zhao, Jing Gao:
BlendFilter: Advancing Retrieval-Augmented Large Language Models via Query Generation Blending and Knowledge Filtering. EMNLP 2024: 1009-1025 - [c109]Alexander Bukharin, Shiyang Li, Zhengyang Wang, Jingfeng Yang, Bing Yin, Xian Li, Chao Zhang, Tuo Zhao, Haoming Jiang:
Data Diversity Matters for Robust Instruction Tuning. EMNLP (Findings) 2024: 3411-3425 - [c108]Tuo Zhao, Xinxue Wang, Tingting Zhao, Yuan Wang, Yarui Chen, Jucheng Yang:
Hybrid Deep Generative and Sequential Learning Approach for Stock Market Prediction. ICIC (LNAI 5) 2024: 263-274 - [c107]Yixiao Li, Yifan Yu, Chen Liang, Nikos Karampatziakis, Pengcheng He, Weizhu Chen, Tuo Zhao:
LoftQ: LoRA-Fine-Tuning-aware Quantization for Large Language Models. ICLR 2024 - [c106]Qingru Zhang, Chandan Singh, Liyuan Liu, Xiaodong Liu, Bin Yu, Jianfeng Gao, Tuo Zhao:
Tell Your Model Where to Attend: Post-hoc Attention Steering for LLMs. ICLR 2024 - [c105]Zichong Li, Qunzhi Xu, Zhenghao Xu, Yajun Mei, Tuo Zhao, Hongyuan Zha:
Beyond Point Prediction: Score Matching-based Pseudolikelihood Estimation of Neural Marked Spatio-Temporal Point Process. ICML 2024 - [c104]Zi-Hao Qiu, Siqi Guo, Mao Xu, Tuo Zhao, Lijun Zhang, Tianbao Yang:
To Cool or not to Cool? Temperature Network Meets Large Foundation Models via DRO. ICML 2024 - [c103]Zhen Shao, Tuo Zhao, Lin Zhang, Yu Liu:
Trust in Digital Commerce: the Moderating Effect of Blockchain Teability Labels. PACIS 2024 - [i120]Haoyu Wang, Tuo Zhao, Jing Gao:
BlendFilter: Advancing Retrieval-Augmented Large Language Models via Query Generation Blending and Knowledge Filtering. CoRR abs/2402.11129 (2024) - [i119]Hao Kang, Qingru Zhang, Souvik Kundu, Geonhwa Jeong, Zaoxing Liu, Tushar Krishna, Tuo Zhao:
GEAR: An Efficient KV Cache Compression Recipe for Near-Lossless Generative Inference of LLM. CoRR abs/2403.05527 (2024) - [i118]Hoang Huy Nguyen, Yan Li, Tuo Zhao:
Stochastic Constrained Decentralized Optimization for Machine Learning with Fewer Data Oracles: a Gradient Sliding Approach. CoRR abs/2404.02511 (2024) - [i117]Zi-Hao Qiu, Siqi Guo, Mao Xu, Tuo Zhao, Lijun Zhang, Tianbao Yang:
To Cool or not to Cool? Temperature Network Meets Large Foundation Models via DRO. CoRR abs/2404.04575 (2024) - [i116]Ilgee Hong, Zichong Li, Alexander Bukharin, Yixiao Li, Haoming Jiang, Tianbao Yang, Tuo Zhao:
Adaptive Preference Scaling for Reinforcement Learning with Human Feedback. CoRR abs/2406.02764 (2024) - [i115]Haoyu Wang, Tianci Liu, Tuo Zhao, Jing Gao:
RoseLoRA: Row and Column-wise Sparse Low-rank Adaptation of Pre-trained Language Model for Knowledge Editing and Fine-tuning. CoRR abs/2406.10777 (2024) - [i114]Alexander Bukharin, Ilgee Hong, Haoming Jiang, Qingru Zhang, Zixuan Zhang, Tuo Zhao:
Robust Reinforcement Learning from Corrupted Human Feedback. CoRR abs/2406.15568 (2024) - [i113]Qingru Zhang, Xiaodong Yu, Chandan Singh, Xiaodong Liu, Liyuan Liu, Jianfeng Gao, Tuo Zhao, Dan Roth, Hao Cheng:
Model Tells Itself Where to Attend: Faithfulness Meets Automatic Attention Steering. CoRR abs/2409.10790 (2024) - [i112]Kuan Wang, Alexander Bukharin, Haoming Jiang, Qingyu Yin, Zhengyang Wang, Tuo Zhao, Jingbo Shang, Chao Zhang, Bing Yin, Xian Li, Jianshu Chen, Shiyang Li:
RNR: Teaching Large Language Models to Follow Roles and Rules. CoRR abs/2409.13733 (2024) - [i111]Zhenghao Xu, Yuqing Wang, Tuo Zhao, Rachel Ward, Molei Tao:
Provable Acceleration of Nesterov's Accelerated Gradient for Rectangular Matrix Factorization and Linear Neural Networks. CoRR abs/2410.09640 (2024) - 2023
- [j22]Ethan X. Fang, Yajun Mei, Yuyang Shi, Qunzhi Xu, Tuo Zhao:
Pivotal Estimation of Linear Discriminant Analysis in High Dimensions. J. Mach. Learn. Res. 24: 302:1-302:45 (2023) - [j21]Guanghui Lan, Yan Li, Tuo Zhao:
Block Policy Mirror Descent. SIAM J. Optim. 33(3): 2341-2378 (2023) - [c102]Simiao Zuo, Qingyu Yin, Haoming Jiang, Shaohui Xi, Bing Yin, Chao Zhang, Tuo Zhao:
Context-Aware Query Rewriting for Improving Users' Search Experience on E-commerce Websites. ACL (industry) 2023: 616-628 - [c101]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:
Reinforcement Learning for Adaptive Mesh Refinement. AISTATS 2023: 5997-6014 - [c100]Qingru Zhang, Dhananjay Ram, Cole Hawkins, Sheng Zha, Tuo Zhao:
Efficient Long-Range Transformers: You Need to Attend More, but Not Necessarily at Every Layer. EMNLP (Findings) 2023: 2775-2786 - [c99]Haoyu Wang, Yaqing Wang, Tianci Liu, Tuo Zhao, Jing Gao:
HadSkip: Homotopic and Adaptive Layer Skipping of Pre-trained Language Models for Efficient Inference. EMNLP (Findings) 2023: 4283-4294 - [c98]Suliang Bu, Tuo Zhao, Yunxin Zhao:
Joint Estimation of DOA and Distance in Noisy Reverberant Conditions. ICASSP 2023: 1-5 - [c97]Xiang Ji, Minshuo Chen, Mengdi Wang, Tuo Zhao:
Sample Complexity of Nonparametric Off-Policy Evaluation on Low-Dimensional Manifolds using Deep Networks. ICLR 2023 - [c96]Chen Liang, Haoming Jiang, Zheng Li, Xianfeng Tang, Bing Yin, Tuo Zhao:
HomoDistil: Homotopic Task-Agnostic Distillation of Pre-trained Transformers. ICLR 2023 - [c95]Qingru Zhang, Minshuo Chen, Alexander Bukharin, Pengcheng He, Yu Cheng, Weizhu Chen, Tuo Zhao:
Adaptive Budget Allocation for Parameter-Efficient Fine-Tuning. ICLR 2023 - [c94]Alexander Bukharin, Tianyi Liu, Shengjie Wang, Simiao Zuo, Weihao Gao, Wen Yan, Tuo Zhao:
Machine Learning Force Fields with Data Cost Aware Training. ICML 2023: 3219-3232 - [c93]Minshuo Chen, Kaixuan Huang, Tuo Zhao, Mengdi Wang:
Score Approximation, Estimation and Distribution Recovery of Diffusion Models on Low-Dimensional Data. ICML 2023: 4672-4712 - [c92]Zichong Li, Yanbo Xu, Simiao Zuo, Haoming Jiang, Chao Zhang, Tuo Zhao, Hongyuan Zha:
SMURF-THP: Score Matching-based UnceRtainty quantiFication for Transformer Hawkes Process. ICML 2023: 20210-20220 - [c91]Yixiao Li, Yifan Yu, Qingru Zhang, Chen Liang, Pengcheng He, Weizhu Chen, Tuo Zhao:
LoSparse: Structured Compression of Large Language Models based on Low-Rank and Sparse Approximation. ICML 2023: 20336-20350 - [c90]Chen Liang, Simiao Zuo, Qingru Zhang, Pengcheng He, Weizhu Chen, Tuo Zhao:
Less is More: Task-aware Layer-wise Distillation for Language Model Compression. ICML 2023: 20852-20867 - [c89]Zixuan Zhang, Minshuo Chen, Mengdi Wang, Wenjing Liao, Tuo Zhao:
Effective Minkowski Dimension of Deep Nonparametric Regression: Function Approximation and Statistical Theories. ICML 2023: 40911-40931 - [c88]Haoyu Wang, Ruirui Li, Haoming Jiang, Zhengyang Wang, Xianfeng Tang, Bin Bi, Monica Xiao Cheng, Bing Yin, Yaqing Wang, Tuo Zhao, Jing Gao:
LightToken: A Task and Model-agnostic Lightweight Token Embedding Framework for Pre-trained Language Models. KDD 2023: 2302-2313 - [c87]Chen Liang, Jiahui Yu, Ming-Hsuan Yang, Matthew Brown, Yin Cui, Tuo Zhao, Boqing Gong, Tianyi Zhou:
Module-wise Adaptive Distillation for Multimodality Foundation Models. NeurIPS 2023 - [c86]Alexander Bukharin, Yan Li, Yue Yu, Qingru Zhang, Zhehui Chen, Simiao Zuo, Chao Zhang, Songan Zhang, Tuo Zhao:
Robust Multi-Agent Reinforcement Learning via Adversarial Regularization: Theoretical Foundation and Stable Algorithms. NeurIPS 2023 - [c85]Shenao Zhang, Boyi Liu, Zhaoran Wang, Tuo Zhao:
Model-Based Reparameterization Policy Gradient Methods: Theory and Practical Algorithms. NeurIPS 2023 - [i110]Minshuo Chen, Kaixuan Huang, Tuo Zhao, Mengdi Wang:
Score Approximation, Estimation and Distribution Recovery of Diffusion Models on Low-Dimensional Data. CoRR abs/2302.07194 (2023) - [i109]Chen Liang, Haoming Jiang, Zheng Li, Xianfeng Tang, Bin Yin, Tuo Zhao:
HomoDistil: Homotopic Task-Agnostic Distillation of Pre-trained Transformers. CoRR abs/2302.09632 (2023) - [i108]Biraj Dahal, Alexander Havrilla, Minshuo Chen, Tuo Zhao, Wenjing Liao:
On Deep Generative Models for Approximation and Estimation of Distributions on Manifolds. CoRR abs/2302.13183 (2023) - [i107]Qingru Zhang, Minshuo Chen, Alexander Bukharin, Pengcheng He, Yu Cheng, Weizhu Chen, Tuo Zhao:
Adaptive Budget Allocation for Parameter-Efficient Fine-Tuning. CoRR abs/2303.10512 (2023) - [i106]Alexander Bukharin, Tianyi Liu, Shengjie Wang, Simiao Zuo, Weihao Gao, Wen Yan, Tuo Zhao:
Machine Learning Force Fields with Data Cost Aware Training. CoRR abs/2306.03109 (2023) - [i105]Yixiao Li, Yifan Yu, Qingru Zhang, Chen Liang, Pengcheng He, Weizhu Chen, Tuo Zhao:
LoSparse: Structured Compression of Large Language Models based on Low-Rank and Sparse Approximation. CoRR abs/2306.11222 (2023) - [i104]Zixuan Zhang, Minshuo Chen, Mengdi Wang, Wenjing Liao, Tuo Zhao:
Effective Minkowski Dimension of Deep Nonparametric Regression: Function Approximation and Statistical Theories. CoRR abs/2306.14859 (2023) - [i103]Kaiqi Zhang, Zixuan Zhang, Minshuo Chen, Mengdi Wang, Tuo Zhao, Yu-Xiang Wang:
Nonparametric Classification on Low Dimensional Manifolds using Overparameterized Convolutional Residual Networks. CoRR abs/2307.01649 (2023) - [i102]Xiang Ji, Huazheng Wang, Minshuo Chen, Tuo Zhao, Mengdi Wang:
Provable Benefits of Policy Learning from Human Preferences in Contextual Bandit Problems. CoRR abs/2307.12975 (2023) - [i101]Alexander Bukharin, Yixiao Li, Pengcheng He, Weizhu Chen, Tuo Zhao:
Deep Reinforcement Learning from Hierarchical Weak Preference Feedback. CoRR abs/2309.02632 (2023) - [i100]Zhenghao Xu, Xiang Ji, Minshuo Chen, Mengdi Wang, Tuo Zhao:
Sample Complexity of Neural Policy Mirror Descent for Policy Optimization on Low-Dimensional Manifolds. CoRR abs/2309.13915 (2023) - [i99]Chen Liang, Jiahui Yu, Ming-Hsuan Yang, Matthew Brown, Yin Cui, Tuo Zhao, Boqing Gong, Tianyi Zhou:
Module-wise Adaptive Distillation for Multimodality Foundation Models. CoRR abs/2310.04550 (2023) - [i98]Yixiao Li, Yifan Yu, Chen Liang, Pengcheng He, Nikos Karampatziakis, Weizhu Chen, Tuo Zhao:
LoftQ: LoRA-Fine-Tuning-Aware Quantization for Large Language Models. CoRR abs/2310.08659 (2023) - [i97]Alexander Bukharin, Yan Li, Yue Yu, Qingru Zhang, Zhehui Chen, Simiao Zuo, Chao Zhang, Songan Zhang, Tuo Zhao:
Robust Multi-Agent Reinforcement Learning via Adversarial Regularization: Theoretical Foundation and Stable Algorithms. CoRR abs/2310.10810 (2023) - [i96]Qingru Zhang, Dhananjay Ram, Cole Hawkins, Sheng Zha, Tuo Zhao:
Efficient Long-Range Transformers: You Need to Attend More, but Not Necessarily at Every Layer. CoRR abs/2310.12442 (2023) - [i95]Zichong Li, Qunzhi Xu, Zhenghao Xu, Yajun Mei, Tuo Zhao, Hongyuan Zha:
Score Matching-based Pseudolikelihood Estimation of Neural Marked Spatio-Temporal Point Process with Uncertainty Quantification. CoRR abs/2310.16310 (2023) - [i94]Zichong Li, Yanbo Xu, Simiao Zuo, Haoming Jiang, Chao Zhang, Tuo Zhao, Hongyuan Zha:
SMURF-THP: Score Matching-based UnceRtainty quantiFication for Transformer Hawkes Process. CoRR abs/2310.16336 (2023) - [i93]Yuqing Wang, Zhenghao Xu, Tuo Zhao, Molei Tao:
Good regularity creates large learning rate implicit biases: edge of stability, balancing, and catapult. CoRR abs/2310.17087 (2023) - [i92]Shenao Zhang, Boyi Liu, Zhaoran Wang, Tuo Zhao:
Model-Based Reparameterization Policy Gradient Methods: Theory and Practical Algorithms. CoRR abs/2310.19927 (2023) - [i91]Qingru Zhang, Chandan Singh, Liyuan Liu, Xiaodong Liu, Bin Yu, Jianfeng Gao, Tuo Zhao:
Tell Your Model Where to Attend: Post-hoc Attention Steering for LLMs. CoRR abs/2311.02262 (2023) - [i90]Alexander Bukharin, Tuo Zhao:
Data Diversity Matters for Robust Instruction Tuning. CoRR abs/2311.14736 (2023) - 2022
- [j20]Zhen Shao, Lin Zhang, Susan A. Brown, Tuo Zhao:
Understanding users' trust transfer mechanism in a blockchain-enabled platform: A mixed methods study. Decis. Support Syst. 155: 113716 (2022) - [j19]Suliang Bu, Yunxin Zhao, Tuo Zhao, Shaojun Wang, Mei Han:
Modeling Speech Structure to Improve T-F Masks for Speech Enhancement and Recognition. IEEE ACM Trans. Audio Speech Lang. Process. 30: 2705-2715 (2022) - [c84]Chen Liang, Pengcheng He, Yelong Shen, Weizhu Chen, Tuo Zhao:
CAMERO: Consistency Regularized Ensemble of Perturbed Language Models with Weight Sharing. ACL (1) 2022: 7162-7175 - [c83]Tianyi Liu, Yan Li, Enlu Zhou, Tuo Zhao:
Noise Regularizes Over-parameterized Rank One Matrix Recovery, Provably. AISTATS 2022: 2784-2802 - [c82]Jiachen Yang, Ethan Wang, Rakshit Trivedi, Tuo Zhao, Hongyuan Zha:
Adaptive Incentive Design with Multi-Agent Meta-Gradient Reinforcement Learning. AAMAS 2022: 1436-1445 - [c81]Yan Li, Dhruv Choudhary, Xiaohan Wei, Baichuan Yuan, Bhargav Bhushanam, Tuo Zhao, Guanghui Lan:
Frequency-aware SGD for Efficient Embedding Learning with Provable Benefits. ICLR 2022 - [c80]Chen Liang, Haoming Jiang, Simiao Zuo, Pengcheng He, Xiaodong Liu, Jianfeng Gao, Weizhu Chen, Tuo Zhao:
No Parameters Left Behind: Sensitivity Guided Adaptive Learning Rate for Training Large Transformer Models. ICLR 2022 - [c79]Yuqing Wang, Minshuo Chen, Tuo Zhao, Molei Tao:
Large Learning Rate Tames Homogeneity: Convergence and Balancing Effect. ICLR 2022 - [c78]Simiao Zuo, Xiaodong Liu, Jian Jiao, Young Jin Kim, Hany Hassan, Ruofei Zhang, Jianfeng Gao, Tuo Zhao:
Taming Sparsely Activated Transformer with Stochastic Experts. ICLR 2022 - [c77]Hao Liu, Minshuo Chen, Siawpeng Er, Wenjing Liao, Tong Zhang, Tuo Zhao:
Benefits of Overparameterized Convolutional Residual Networks: Function Approximation under Smoothness Constraint. ICML 2022: 13669-13703 - [c76]Qingru Zhang, Simiao Zuo, Chen Liang, Alexander Bukharin, Pengcheng He, Weizhu Chen, Tuo Zhao:
PLATON: Pruning Large Transformer Models with Upper Confidence Bound of Weight Importance. ICML 2022: 26809-26823 - [c75]Suliang Bu, Yunxin Zhao, Tuo Zhao:
Steering vector correction in MVDR beamformer for speech enhancement. INTERSPEECH 2022: 5468-5472 - [c74]Zhigen Zhao, Simiao Zuo, Tuo Zhao, Ye Zhao:
Adversarially Regularized Policy Learning Guided by Trajectory Optimization. L4DC 2022: 844-857 - [c73]Rui Feng, Chen Luo, Qingyu Yin, Bing Yin, Tuo Zhao, Chao Zhang:
CERES: Pretraining of Graph-Conditioned Transformer for Semi-Structured Session Data. NAACL-HLT 2022: 219-230 - [c72]Simiao Zuo, Yue Yu, Chen Liang, Haoming Jiang, Siawpeng Er, Chao Zhang, Tuo Zhao, Hongyuan Zha:
Self-Training with Differentiable Teacher. NAACL-HLT (Findings) 2022: 933-949 - [c71]Simiao Zuo, Qingru Zhang, Chen Liang, Pengcheng He, Tuo Zhao, Weizhu Chen:
MoEBERT: from BERT to Mixture-of-Experts via Importance-Guided Adaptation. NAACL-HLT 2022: 1610-1623 - [c70]Biraj Dahal, Alexander Havrilla, Minshuo Chen, Tuo Zhao, Wenjing Liao:
On Deep Generative Models for Approximation and Estimation of Distributions on Manifolds. NeurIPS 2022 - [c69]Suliang Bu, Tuo Zhao, Yunxin Zhao:
TDOA Estimation of Speech Source in Noisy Reverberant Environments. SLT 2022: 1059-1066 - [i89]Hao Liu, Haizhao Yang, Minshuo Chen, Tuo Zhao, Wenjing Liao:
Deep Nonparametric Estimation of Operators between Infinite Dimensional Spaces. CoRR abs/2201.00217 (2022) - [i88]Siawpeng Er, Edward Liu, Minshuo Chen, Yan Li, Yuqi Liu, Tuo Zhao, Hua Wang:
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 abs/2201.02141 (2022) - [i87]Guanghui Lan, Yan Li, Tuo Zhao:
Block Policy Mirror Descent. CoRR abs/2201.05756 (2022) - [i86]Yan Li, Tuo Zhao, Guanghui Lan:
Homotopic Policy Mirror Descent: Policy Convergence, Implicit Regularization, and Improved Sample Complexity. CoRR abs/2201.09457 (2022) - [i85]Chen Liang, Haoming Jiang, Simiao Zuo, Pengcheng He, Xiaodong Liu, Jianfeng Gao, Weizhu Chen, Tuo Zhao:
No Parameters Left Behind: Sensitivity Guided Adaptive Learning Rate for Training Large Transformer Models. CoRR abs/2202.02664 (2022) - [i84]Tianyi Liu, Yan Li, Enlu Zhou, Tuo Zhao:
Noise Regularizes Over-parameterized Rank One Matrix Recovery, Provably. CoRR abs/2202.03535 (2022) - [i83]Rui Feng, Chen Luo, Qingyu Yin, Bing Yin, Tuo Zhao, Chao Zhang:
CERES: Pretraining of Graph-Conditioned Transformer for Semi-Structured Session Data. CoRR abs/2204.04303 (2022) - [i82]Chen Liang, Pengcheng He, Yelong Shen, Weizhu Chen, Tuo Zhao:
CAMERO: Consistency Regularized Ensemble of Perturbed Language Models with Weight Sharing. CoRR abs/2204.06625 (2022) - [i81]Simiao Zuo, Qingru Zhang, Chen Liang, Pengcheng He, Tuo Zhao, Weizhu Chen:
MoEBERT: from BERT to Mixture-of-Experts via Importance-Guided Adaptation. CoRR abs/2204.07675 (2022) - [i80]Jie Wang, Minshuo Chen, Tuo Zhao, Wenjing Liao, Yao Xie:
A Manifold Two-Sample Test Study: Integral Probability Metric with Neural Networks. CoRR abs/2205.02043 (2022) - [i79]Xiang Ji, Minshuo Chen, Mengdi Wang, Tuo Zhao:
Sample Complexity of Nonparametric Off-Policy Evaluation on Low-Dimensional Manifolds using Deep Networks. CoRR abs/2206.02887 (2022) - [i78]Hao Liu, Minshuo Chen, Siawpeng Er, Wenjing Liao, Tong Zhang, Tuo Zhao:
Benefits of Overparameterized Convolutional Residual Networks: Function Approximation under Smoothness Constraint. CoRR abs/2206.04569 (2022) - [i77]Qingru Zhang, Simiao Zuo, Chen Liang, Alexander Bukharin, Pengcheng He, Weizhu Chen, Tuo Zhao:
PLATON: Pruning Large Transformer Models with Upper Confidence Bound of Weight Importance. CoRR abs/2206.12562 (2022) - [i76]Simiao Zuo, Tianyi Liu, Tuo Zhao, Hongyuan Zha:
Differentially Private Estimation of Hawkes Process. CoRR abs/2209.07303 (2022) - [i75]Simiao Zuo, Haoming Jiang, Qingyu Yin, Xianfeng Tang, Bing Yin, Tuo Zhao:
DiP-GNN: Discriminative Pre-Training of Graph Neural Networks. CoRR abs/2209.07499 (2022) - [i74]Simiao Zuo, Qingyu Yin, Haoming Jiang, Shaohui Xi, Bing Yin, Chao Zhang, Tuo Zhao:
Context-Aware Query Rewriting for Improving Users' Search Experience on E-commerce Websites. CoRR abs/2209.07584 (2022) - [i73]Yan Li, Tuo Zhao, Guanghui Lan:
First-order Policy Optimization for Robust Markov Decision Process. CoRR abs/2209.10579 (2022) - [i72]Chen Liang, Simiao Zuo, Qingru Zhang, Pengcheng He, Weizhu Chen, Tuo Zhao:
Less is More: Task-aware Layer-wise Distillation for Language Model Compression. CoRR abs/2210.01351 (2022) - [i71]Jiahui Cheng, Minshuo Chen, Hao Liu, Tuo Zhao, Wenjing Liao:
High Dimensional Binary Classification under Label Shift: Phase Transition and Regularization. CoRR abs/2212.00700 (2022) - [i70]Simiao Zuo, Xiaodong Liu, Jian Jiao, Denis Charles, Eren Manavoglu, Tuo Zhao, Jianfeng Gao:
Efficient Long Sequence Modeling via State Space Augmented Transformer. CoRR abs/2212.08136 (2022) - 2021
- [j18]Lewis Liu, Songtao Lu, Tuo Zhao, Zhaoran Wang:
Spectrum Truncation Power Iteration for Agnostic Matrix Phase Retrieval. IEEE Trans. Signal Process. 69: 3991-4006 (2021) - [c68]Haoming Jiang, Danqing Zhang, Tianyu Cao, Bing Yin, Tuo Zhao:
Named Entity Recognition with Small Strongly Labeled and Large Weakly Labeled Data. ACL/IJCNLP (1) 2021: 1775-1789 - [c67]Chen Liang, Simiao Zuo, Minshuo Chen, Haoming Jiang, Xiaodong Liu, Pengcheng He, Tuo Zhao, Weizhu Chen:
Super Tickets in Pre-Trained Language Models: From Model Compression to Improving Generalization. ACL/IJCNLP (1) 2021: 6524-6538 - [c66]Haoming Jiang, Zhehui Chen, Yuyang Shi, Bo Dai, Tuo Zhao:
Learning to Defend by Learning to Attack. AISTATS 2021: 577-585 - [c65]Tianyi Liu, Yan Li, Song Wei, Enlu Zhou, Tuo Zhao:
Noisy Gradient Descent Converges to Flat Minima for Nonconvex Matrix Factorization. AISTATS 2021: 1891-1899 - [c64]Danqing Zhang, Zheng Li, Tianyu Cao, Chen Luo, Tony Wu, Hanqing Lu, Yiwei Song, Bing Yin, Tuo Zhao, Qiang Yang:
QUEACO: Borrowing Treasures from Weakly-labeled Behavior Data for Query Attribute Value Extraction. CIKM 2021: 4362-4372 - [c63]Chen Liang, Haoming Jiang, Xiaodong Liu, Pengcheng He, Weizhu Chen, Jianfeng Gao, Tuo Zhao:
Token-wise Curriculum Learning for Neural Machine Translation. EMNLP (Findings) 2021: 3658-3670 - [c62]Simiao Zuo, Chen Liang, Haoming Jiang, Pengcheng He, Xiaodong Liu, Jianfeng Gao, Weizhu Chen, Tuo Zhao:
ARCH: Efficient Adversarial Regularized Training with Caching. EMNLP (Findings) 2021: 4118-4131 - [c61]Simiao Zuo, Chen Liang, Haoming Jiang, Xiaodong Liu, Pengcheng He, Jianfeng Gao, Weizhu Chen, Tuo Zhao:
Adversarial Regularization as Stackelberg Game: An Unrolled Optimization Approach. EMNLP (1) 2021: 6562-6577 - [c60]Haoming Jiang, Bo Dai, Mengjiao Yang, Tuo Zhao, Wei Wei:
Towards Automatic Evaluation of Dialog Systems: A Model-Free Off-Policy Evaluation Approach. EMNLP (1) 2021: 7419-7451 - [c59]