Yu-Xiang Wang

Publication Activity (10 Years)

Years Active: 2019-2024
Publications (10 Years): 52

Top Topics

Language Generation

Differentially Private

Nearest Neighbor

Reinforcement Learning

Top Venues

J. Mach. Learn. Res.

Publications

Dan Qiao, Yu-Xiang Wang
Near-Optimal Reinforcement Learning with Self-Play under Adaptivity Constraints. CoRR (2024)
Ruihan Wu, Siddhartha Datta, Yi Su, Dheeraj Baby, Yu-Xiang Wang, Kilian Q. Weinberger
Online Feature Updates Improve Online (Generalized) Label Shift Adaptation. CoRR (2024)
Xuandong Zhao, Lei Li, Yu-Xiang Wang
Permute-and-Flip: An optimally robust and watermarkable decoder for LLMs. CoRR (2024)
Xuandong Zhao, Xianjun Yang, Tianyu Pang, Chao Du, Lei Li, Yu-Xiang Wang, William Yang Wang
Weak-to-Strong Jailbreaking on Large Language Models. CoRR (2024)
Ming Yin, Mengdi Wang, Yu-Xiang Wang
Offline Reinforcement Learning with Differentiable Function Approximation is Provably Efficient. ICLR (2023)
Kaiqi Zhang, Yu-Xiang Wang
Deep Learning meets Nonparametric Regression: Are Weight-Decayed DNNs Locally Adaptive? ICLR (2023)
Dan Qiao, Yu-Xiang Wang
Offline Reinforcement Learning with Differential Privacy. NeurIPS (2023)
Sunil Madhow, Dan Xiao, Ming Yin, Yu-Xiang Wang
Offline Policy Evaluation for Reinforcement Learning with Adaptively Collected Data. CoRR (2023)
Chong Liu, Yu-Xiang Wang
Global Optimization with Parametric Function Approximation. ICML (2023)
Jianyu Xu, Yu-Xiang Wang
Pricing with Contextual Elasticity and Heteroscedastic Valuation. CoRR (2023)
Songtao Feng, Ming Yin, Ruiquan Huang, Yu-Xiang Wang, Jing Yang, Yingbin Liang
Non-stationary Reinforcement Learning under General Function Approximation. ICML (2023)
Xuandong Zhao, Yu-Xiang Wang, Lei Li
Protecting Language Generation Models via Invisible Watermarking. CoRR (2023)
Meng-Chang Wu, Yu-Xiang Wang, Yung-Hoh Sheu, Ching-Lin Li, Teng-Chi Chang, Jen-Yu Shieh
LCM Aging Detection and Analysis System Design. ICCE-Taiwan (2023)
Chong Liu, Ming Yin, Yu-Xiang Wang
No-Regret Linear Bandits beyond Realizability. UAI (2023)
Chong Liu, Ming Yin, Yu-Xiang Wang
No-Regret Linear Bandits beyond Realizability. CoRR (2023)
Yuqing Zhu, Xuandong Zhao, Chuan Guo, Yu-Xiang Wang
Private Prediction Strikes Back! Private Kernelized Nearest Neighbors with Individual Rényi Filter. UAI (2023)
Songtao Feng, Ming Yin, Yu-Xiang Wang, Jing Yang, Yingbin Liang
Model-Free Algorithm with Improved Sample Efficiency for Zero-Sum Markov Games. CoRR (2023)
Xuandong Zhao, Kexun Zhang, Yu-Xiang Wang, Lei Li
Generative Autoencoders as Watermark Attackers: Analyses of Vulnerabilities and Threats. CoRR (2023)
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 (2023)
Xuandong Zhao, Yu-Xiang Wang, Lei Li
Protecting Language Generation Models via Invisible Watermarking. ICML (2023)
Peng Zhao, Yu-Hu Yan, Yu-Xiang Wang, Zhi-Hua Zhou
Non-stationary Online Learning with Memory and Non-stochastic Control. J. Mach. Learn. Res. 24 (2023)
Shuai Tang, Sergül Aydöre, Michael Kearns, Saeyoung Rho, Aaron Roth, Yichen Wang, Yu-Xiang Wang, Zhiwei Steven Wu
Improved Differentially Private Regression via Gradient Boosting. CoRR (2023)
Songtao Feng, Ming Yin, Ruiquan Huang, Yu-Xiang Wang, Jing Yang, Yingbin Liang
Non-stationary Reinforcement Learning under General Function Approximation. CoRR (2023)
Yuqing Zhu, Xuandong Zhao, Chuan Guo, Yu-Xiang Wang
"Private Prediction Strikes Back!" Private Kernelized Nearest Neighbors with Individual Renyi Filter. CoRR (2023)
Zhiqi Bu, Yu-Xiang Wang, Sheng Zha, George Karypis
Differentially Private Optimization on Large Model at Small Cost. ICML (2023)
Dan Qiao, Ming Yin, Yu-Xiang Wang
Logarithmic Switching Cost in Reinforcement Learning beyond Linear MDPs. CoRR (2023)
Jiachen Li, Edwin Zhang, Ming Yin, Qinxun Bai, Yu-Xiang Wang, William Yang Wang
Offline Reinforcement Learning with Closed-Form Policy Improvement Operators. ICML (2023)
Xuandong Zhao, Prabhanjan Ananth, Lei Li, Yu-Xiang Wang
Provable Robust Watermarking for AI-Generated Text. CoRR (2023)
Rachel Cummings, Damien Desfontaines, David Evans, Roxana Geambasu, Matthew Jagielski, Yangsibo Huang, Peter Kairouz, Gautam Kamath, Sewoong Oh, Olga Ohrimenko, Nicolas Papernot, Ryan Rogers, Milan Shen, Shuang Song, Weijie J. Su, Andreas Terzis, Abhradeep Thakurta, Sergei Vassilvitskii, Yu-Xiang Wang, Li Xiong, Sergey Yekhanin, Da Yu, Huanyu Zhang, Wanrong Zhang
Challenges towards the Next Frontier in Privacy. CoRR (2023)
Yuqing Zhu, Yu-Xiang Wang
Adaptive Private-K-Selection with Adaptive K and Application to Multi-label PATE. AISTATS (2022)
Zhiqi Bu, Yu-Xiang Wang, Sheng Zha, George Karypis
Differentially Private Bias-Term only Fine-tuning of Foundation Models. CoRR (2022)
Zhiqi Bu, Yu-Xiang Wang, Sheng Zha, George Karypis
Automatic Clipping: Differentially Private Deep Learning Made Easier and Stronger. CoRR (2022)
Zhiqi Bu, Yu-Xiang Wang, Sheng Zha, George Karypis
Differentially Private Optimization on Large Model at Small Cost. CoRR (2022)
Zhiliang Tian, Yingxiu Zhao, Ziyue Huang, Yu-Xiang Wang, Nevin L. Zhang, He He
SeqPATE: Differentially Private Text Generation via Knowledge Distillation. NeurIPS (2022)
Jianyu Xu, Dan Qiao, Yu-Xiang Wang
Doubly Fair Dynamic Pricing. CoRR (2022)
Chong Liu, Yu-Xiang Wang
Doubly Robust Crowdsourcing. J. Artif. Intell. Res. 73 (2022)
Kaiqi Zhang, Ming Yin, Yu-Xiang Wang
Why Quantization Improves Generalization: NTK of Binary Weight Neural Networks. CoRR (2022)
Aditya Golatkar, Alessandro Achille, Yu-Xiang Wang, Aaron Roth, Michael Kearns, Stefano Soatto
Mixed Differential Privacy in Computer Vision. CVPR (2022)
Jianyu Xu, Yu-Xiang Wang
Towards Agnostic Feature-based Dynamic Pricing: Linear Policies vs Linear Valuation with Unknown Noise. AISTATS (2022)
Yuqing Zhu, Jinshuo Dong, Yu-Xiang Wang
Optimal Accounting of Differential Privacy via Characteristic Function. AISTATS (2022)
Jiachen Li, Edwin Zhang, Ming Yin, Qinxun Bai, Yu-Xiang Wang, William Yang Wang
Offline Reinforcement Learning with Closed-Form Policy Improvement Operators. CoRR (2022)
Jianyu Xu, Yu-Xiang Wang
Towards Agnostic Feature-based Dynamic Pricing: Linear Policies vs Linear Valuation with Unknown Noise. CoRR (2022)
Yuqing Zhu, Yu-Xiang Wang
Adaptive Private-K-Selection with Adaptive K and Application to Multi-label PATE. CoRR (2022)
Kaiqi Zhang, Yu-Xiang Wang
Deep Learning meets Nonparametric Regression: Are Weight-Decayed DNNs Locally Adaptive? CoRR (2022)
Simone Bombari, Alessandro Achille, Zijian Wang, Yu-Xiang Wang, Yusheng Xie, Kunwar Yashraj Singh, Srikar Appalaraju, Vijay Mahadevan, Stefano Soatto
Towards Differential Relational Privacy and its use in Question Answering. CoRR (2022)
Dan Qiao, Yu-Xiang Wang
Near-Optimal Deployment Efficiency in Reward-Free Reinforcement Learning with Linear Function Approximation. CoRR (2022)
Aditya Golatkar, Alessandro Achille, Yu-Xiang Wang, Aaron Roth, Michael Kearns, Stefano Soatto
Mixed Differential Privacy in Computer Vision. CoRR (2022)
Xuandong Zhao, Lei Li, Yu-Xiang Wang
Distillation-Resistant Watermarking for Model Protection in NLP. EMNLP (Findings) (2022)
Hsien-Hua Liao, Chi-Chang Chang, Yu-Xiang Wang, Chalong Cheewakriangkrai
Predicting the Risk Factors of Second Primary Cancer in Patients with Hepatocellular Carcinoma. ICIMTH (2021)
Rachel Redberg, Yu-Xiang Wang
Privately Publishable Per-instance Privacy. CoRR (2021)
Chong Liu, Yuqing Zhu, Kamalika Chaudhuri, Yu-Xiang Wang
Revisiting Model-Agnostic Private Learning: Faster Rates and Active Learning. J. Mach. Learn. Res. 22 (2021)
Chong Liu, Yu-Xiang Wang
Doubly Robust Crowdsourcing. CoRR (2019)