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Yu-Xiang Wang

108 papers · 2013–2025 · 12 conferences · across top CS/AI conferences

Achievements

🐝 Cross-Pollinator (10) 🌈 Renaissance Researcher (5) πŸŒ‰ Interdisciplinary Bridge πŸ—ΊοΈ Taxonomy Completionist (30) 🧭 Keyword Pioneer 🐣 Hot Topic Early Bird 🌍 Conference Polyglot (12) πŸƒ Academic Marathon (12) 🏠 Conference Loyalist (33) πŸ† Keyword Champion (3) πŸ‘‘ Triple Crown 🀝 Dynamic Duo (16) πŸ”¬ Deep Specialist (11) ❓ The Questioner πŸ’Ž Century Club (108) ⚑ Prolific Year (22) πŸš€ Conference Pioneer πŸ“ˆ Trend Setter πŸ”₯ Unstoppable (13) πŸ—ƒοΈ Keyword Collector (104)

Conferences

NIPS (33) ICML (28) AISTATS (21) ICLR (9) JMLR (5) CVPR (3) UAI (3) ACL (2) COLT (1) EMNLP (1) L4DC (1) NAACL (1)

Top co-authors

Ming Yin (16) Yuqing Zhu (12) Dheeraj Baby (12) Xuandong Zhao (11) Dan Qiao (10) Lei Li (9) Chong Liu (5) Mengdi Wang (5) Zhiqi Bu (4) Jianyu Xu (4)

Research topics

Differential Privacy (11) Privacy (3) Computer Vision (1) Statistics (1) Optimization & Theory (1)

Keywords

differential privacy (24) online learning (13) regret bound (10) dynamic regret (9) offline reinforcement learning (8) total variation (7) markov decision process (6) subspace clustering (5) reinforcement learning (5) switching cost (4) privacy-preserving machine learning (4) trend filtering (4) knowledge distillation (4) domain adaptation (4) privacy preservation (4) off-policy evaluation (4) sparse subspace clustering (4) convex optimization (4) sparse representation (3) time series forecasting (3)

Papers

Adapting to Online Distribution Shifts in Deep Learning: A Black-Box Approach AISTATS 2025
Rates for Offline Reinforcement Learning with Adaptively Collected Data L4DC 2025
Weak-to-Strong Jailbreaking on Large Language Models ICML 2025
Adapting to Linear Separable Subsets with Large-Margin in Differentially Private Learning ICML 2025
AKORN: Adaptive Knots generated Online for RegressioN splines ICML 2025
PROXSPARSE: REGULARIZED LEARNING OF SEMI-STRUCTURED SPARSITY MASKS FOR PRETRAINED LLMS ICML 2025
Adaptive Estimation and Learning under Temporal Distribution Shift ICML 2025
Efficiently Identifying Watermarked Segments in Mixed-Source Texts ACL 2025
Permute-and-Flip: An optimally stable and watermarkable decoder for LLMs ICLR 2025
Privacy Profiles for Private Selection ICML 2024
Improving Sample Efficiency of Model-Free Algorithms for Zero-Sum Markov Games ICML 2024
Differentially Private Bias-Term Fine-tuning of Foundation Models ICML 2024
Provable Robust Watermarking for AI-Generated Text ICLR 2024
Communication-Efficient Federated Non-Linear Bandit Optimization ICLR 2024
Tractable MCMC for Private Learning with Pure and Gaussian Differential Privacy ICLR 2024
CPR: Retrieval Augmented Generation for Copyright Protection CVPR 2024
Pricing with Contextual Elasticity and Heteroscedastic Valuation ICML 2024
Template-free Articulated Gaussian Splatting for Real-time Reposable Dynamic View Synthesis NIPS 2024
Invisible Image Watermarks Are Provably Removable Using Generative AI NIPS 2024
Nonparametric Classification on Low Dimensional Manifolds using Overparameterized Convolutional Residual Networks NIPS 2024
Differentially Private Reinforcement Learning with Self-Play NIPS 2024
Stable Minima Cannot Overfit in Univariate ReLU Networks: Generalization by Large Step Sizes NIPS 2024
NetworkGym: Reinforcement Learning Environments for Multi-Access Traffic Management in Network Simulation NIPS 2024
Online Feature Updates Improve Online (Generalized) Label Shift Adaptation NIPS 2024
Watermarking for Large Language Models ACL 2024
Neural Collapse meets Differential Privacy: Curious behaviors of NoisyGD with Near-Perfect Representation Learning ICML 2024
Near-Optimal Reinforcement Learning with Self-Play under Adaptivity Constraints ICML 2024
Private Prediction Strikes Back! Private Kernelized Nearest Neighbors with Individual RΓ©nyi Filter UAI 2023
Posterior Sampling with Delayed Feedback for Reinforcement Learning with Linear Function Approximation NIPS 2023
Improving the Privacy and Practicality of Objective Perturbation for Differentially Private Linear Learners NIPS 2023
An Efficient and Robust Framework for Approximate Nearest Neighbor Search with Attribute Constraint NIPS 2023
Automatic Clipping: Differentially Private Deep Learning Made Easier and Stronger NIPS 2023
A Privacy-Friendly Approach to Data Valuation NIPS 2023
Offline Reinforcement Learning with Differential Privacy NIPS 2023
Online Label Shift: Optimal Dynamic Regret meets Practical Algorithms NIPS 2023
Generalized PTR: User-Friendly Recipes for Data-Adaptive Algorithms with Differential Privacy AISTATS 2023
Second Order Path Variationals in Non-Stationary Online Learning AISTATS 2023
Near-Optimal Differentially Private Reinforcement Learning AISTATS 2023
Doubly Fair Dynamic Pricing AISTATS 2023
Offline Reinforcement Learning with Differentiable Function Approximation is Provably Efficient ICLR 2023
Near-Optimal Deployment Efficiency in Reward-Free Reinforcement Learning with Linear Function Approximation ICLR 2023
Deep Learning meets Nonparametric Regression: Are Weight-Decayed DNNs Locally Adaptive? ICLR 2023
Differentially Private Optimization on Large Model at Small Cost ICML 2023
Non-stationary Reinforcement Learning under General Function Approximation ICML 2023
Offline Reinforcement Learning with Closed-Form Policy Improvement Operators ICML 2023
Global Optimization with Parametric Function Approximation ICML 2023
Protecting Language Generation Models via Invisible Watermarking ICML 2023
Non-stationary Online Learning with Memory and Non-stochastic Control JMLR 2023
No-Regret Linear Bandits beyond Realizability UAI 2023
Optimal Accounting of Differential Privacy via Characteristic Function AISTATS 2022
Sample-Efficient Reinforcement Learning with loglog(T) Switching Cost ICML 2022
Provably Confidential Language Modelling NAACL 2022
Non-stationary Online Learning with Memory and Non-stochastic Control AISTATS 2022
Optimal Dynamic Regret in LQR Control NIPS 2022
Mixed Differential Privacy in Computer Vision CVPR 2022
Differentially Private Linear Sketches: Efficient Implementations and Applications NIPS 2022
Distillation-Resistant Watermarking for Model Protection in NLP EMNLP 2022
Towards Agnostic Feature-based Dynamic Pricing: Linear Policies vs Linear Valuation with Unknown Noise AISTATS 2022
Near-optimal Offline Reinforcement Learning with Linear Representation: Leveraging Variance Information with Pessimism ICLR 2022
Optimal Dynamic Regret in Proper Online Learning with Strongly Convex Losses and Beyond AISTATS 2022
SeqPATE: Differentially Private Text Generation via Knowledge Distillation NIPS 2022
Adaptive Private-K-Selection with Adaptive K and Application to Multi-label PATE AISTATS 2022
Offline stochastic shortest path: Learning, evaluation and towards optimality UAI 2022
Near-Optimal Provable Uniform Convergence in Offline Policy Evaluation for Reinforcement Learning AISTATS 2021
Revisiting Model-Agnostic Private Learning: Faster Rates and Active Learning AISTATS 2021
An Optimal Reduction of TV-Denoising to Adaptive Online Learning AISTATS 2021
Near-Optimal Offline Reinforcement Learning via Double Variance Reduction NIPS 2021
Towards Instance-Optimal Offline Reinforcement Learning with Pessimism NIPS 2021
Revisiting Model-Agnostic Private Learning: Faster Rates and Active Learning JMLR 2021
Privately Publishable Per-instance Privacy NIPS 2021
Logarithmic Regret in Feature-based Dynamic Pricing NIPS 2021
Optimal Uniform OPE and Model-based Offline Reinforcement Learning in Time-Homogeneous, Reward-Free and Task-Agnostic Settings NIPS 2021
Optimal Dynamic Regret in Exp-Concave Online Learning COLT 2021
Improving Sparse Vector Technique with Renyi Differential Privacy NIPS 2020
An end-to-end Differentially Private Latent Dirichlet Allocation Using a Spectral Algorithm ICML 2020
Private-kNN: Practical Differential Privacy for Computer Vision CVPR 2020
Asymptotically Efficient Off-Policy Evaluation for Tabular Reinforcement Learning AISTATS 2020
Domain Adaptation with Conditional Distribution Matching and Generalized Label Shift NIPS 2020
Adaptive Online Estimation of Piecewise Polynomial Trends NIPS 2020
Imitation-Regularized Offline Learning AISTATS 2019
Towards Optimal Off-Policy Evaluation for Reinforcement Learning with Marginalized Importance Sampling NIPS 2019
Provably Efficient Q-Learning with Low Switching Cost NIPS 2019
ProxQuant: Quantized Neural Networks via Proximal Operators ICLR 2019
Poission Subsampled RΓ©nyi Differential Privacy ICML 2019
Enhancing the Locality and Breaking the Memory Bottleneck of Transformer on Time Series Forecasting NIPS 2019
Online Forecasting of Total-Variation-bounded Sequences NIPS 2019
Subsampled Renyi Differential Privacy and Analytical Moments Accountant AISTATS 2019
A Higher-Order Kolmogorov-Smirnov Test AISTATS 2019
Improving the Gaussian Mechanism for Differential Privacy: Analytical Calibration and Optimal Denoising ICML 2018
Detecting and Correcting for Label Shift with Black Box Predictors ICML 2018
signSGD: Compressed Optimisation for Non-Convex Problems ICML 2018
Attributing Hacks AISTATS 2017
Optimal and Adaptive Off-policy Evaluation in Contextual Bandits ICML 2017
Higher-Order Total Variation Classes on Grids: Minimax Theory and Trend Filtering Methods NIPS 2017
Graph Connectivity in Noisy Sparse Subspace Clustering AISTATS 2016
Graph Sparsification Approaches for Laplacian Smoothing AISTATS 2016
Total Variation Classes Beyond 1d: Minimax Rates, and the Limitations of Linear Smoothers NIPS 2016
Parallel and Distributed Block-Coordinate Frank-Wolfe Algorithms ICML 2016
Trend Filtering on Graphs JMLR 2016
Noisy Sparse Subspace Clustering JMLR 2016
Learning with Differential Privacy: Stability, Learnability and the Sufficiency and Necessity of ERM Principle JMLR 2016
Differentially private subspace clustering NIPS 2015
Privacy for Free: Posterior Sampling and Stochastic Gradient Monte Carlo ICML 2015
Trend Filtering on Graphs AISTATS 2015
A Deterministic Analysis of Noisy Sparse Subspace Clustering for Dimensionality-reduced Data ICML 2015
The Falling Factorial Basis and Its Statistical Applications ICML 2014
Noisy Sparse Subspace Clustering ICML 2013
Provable Subspace Clustering: When LRR meets SSC NIPS 2013