Wang, Tianhao

31 publications

ICLRW 2025 Benchmarking Differentially Private Tabular Data Synthesis Algorithms Kai Chen, Xiaochen Li, Chen Gong, Ryan McKenna, Tianhao Wang

ICLR 2025 Can Neural Networks Achieve Optimal Computational-Statistical Tradeoff? an Analysis on Single-Index Model Siyu Chen, Beining Wu, Miao Lu, Zhuoran Yang, Tianhao Wang

ICLR 2025 Data-Adaptive Differentially Private Prompt Synthesis for In-Context Learning Fengyu Gao, Ruida Zhou, Tianhao Wang, Cong Shen, Jing Yang

AISTATS 2025 How Well Can Transformers Emulate In-Context Newton’s Method? Angeliki Giannou, Liu Yang, Tianhao Wang, Dimitris Papailiopoulos, Jason D. Lee

ICLR 2025 Predictive Uncertainty Quantification for Bird's Eye View Segmentation: A Benchmark and Novel Loss Function Linlin Yu, Bowen Yang, Tianhao Wang, Kangshuo Li, Feng Chen

ICML 2025 Structured Preconditioners in Adaptive Optimization: A Unified Analysis Shuo Xie, Tianhao Wang, Sashank J. Reddi, Sanjiv Kumar, Zhiyuan Li

AAAI 2024 Backdoor Attacks via Machine Unlearning Zihao Liu, Tianhao Wang, Mengdi Huai, Chenglin Miao

NeurIPSW 2024 Can Neural Networks Achieve Optimal Computational-Statistical Tradeoff? an Analysis on Single-Index Model Siyu Chen, Beining Wu, Miao Lu, Zhuoran Yang, Tianhao Wang

ICLR 2024 The Marginal Value of Momentum for Small Learning Rate SGD Runzhe Wang, Sadhika Malladi, Tianhao Wang, Kaifeng Lyu, Zhiyuan Li

ICML 2024 Towards Certified Unlearning for Deep Neural Networks Binchi Zhang, Yushun Dong, Tianhao Wang, Jundong Li

NeurIPS 2024 Unveiling Induction Heads: Provable Training Dynamics and Feature Learning in Transformers Siyu Chen, Heejune Sheen, Tianhao Wang, Zhuoran Yang

ICMLW 2024 Unveiling Induction Heads: Provable Training Dynamics and Feature Learning in Transformers Siyu Chen, Heejune Sheen, Tianhao Wang, Zhuoran Yang

ICML 2023 Cooperative Multi-Agent Reinforcement Learning: Asynchronous Communication and Linear Function Approximation Yifei Min, Jiafan He, Tianhao Wang, Quanquan Gu

AISTATS 2023 Finding Regularized Competitive Equilibria of Heterogeneous Agent Macroeconomic Models via Reinforcement Learning Ruitu Xu, Yifei Min, Tianhao Wang, Michael I. Jordan, Zhaoran Wang, Zhuoran Yang

NeurIPS 2023 GlucoSynth: Generating Differentially-Private Synthetic Glucose Traces Josephine Lamp, Mark Derdzinski, Christopher Hannemann, Joost van der Linden, Lu Feng, Tianhao Wang, David Evans

ICLR 2023 Is Adversarial Training Really a Silver Bullet for Mitigating Data Poisoning? Rui Wen, Zhengyu Zhao, Zhuoran Liu, Michael Backes, Tianhao Wang, Yang Zhang

ICLR 2023 LAVA: Data Valuation Without Pre-Specified Learning Algorithms Hoang Anh Just, Feiyang Kang, Tianhao Wang, Yi Zeng, Myeongseob Ko, Ming Jin, Ruoxi Jia

NeurIPS 2023 Noise-Adaptive Thompson Sampling for Linear Contextual Bandits Ruitu Xu, Yifei Min, Tianhao Wang

ICCVW 2023 The Robust Semantic Segmentation UNCV2023 Challenge Results Xuanlong Yu, Yi Zuo, Zitao Wang, Xiaowen Zhang, Jiaxuan Zhao, Yuting Yang, Licheng Jiao, Rui Peng, Xinyi Wang, Junpei Zhang, Kexin Zhang, Fang Liu, Roberto Alcover-Couso, Juan C. SanMiguel, Marcos Escudero-Viñolo, Hanlin Tian, Kenta Matsui, Tianhao Wang, Fahmy Adan, Zhitong Gao, Xuming He, Quentin Bouniot, Hossein Moghaddam, Shyam Nandan Rai, Fabio Cermelli, Carlo Masone, Andrea Pilzer, Elisa Ricci, Andrei Bursuc, Arno Solin, Martin Trapp, Rui Li, Angela Yao, Wenlong Chen, Ivor Simpson, Neill D. F. Campbell, Gianni Franchi

NeurIPS 2022 A Simple and Provably Efficient Algorithm for Asynchronous Federated Contextual Linear Bandits Jiafan He, Tianhao Wang, Yifei Min, Quanquan Gu

NeurIPS 2022 Fast Mixing of Stochastic Gradient Descent with Normalization and Weight Decay Zhiyuan Li, Tianhao Wang, Dingli Yu

NeurIPS 2022 Implicit Bias of Gradient Descent on Reparametrized Models: On Equivalence to Mirror Descent Zhiyuan Li, Tianhao Wang, Jason Lee, Sanjeev Arora

NeurIPS 2022 Learn to Match with No Regret: Reinforcement Learning in Markov Matching Markets Yifei Min, Tianhao Wang, Ruitu Xu, Zhaoran Wang, Michael I. Jordan, Zhuoran Yang

ICML 2022 Learning Stochastic Shortest Path with Linear Function Approximation Yifei Min, Jiafan He, Tianhao Wang, Quanquan Gu

ICMLW 2022 Memorization in NLP Fine-Tuning Methods Fatemehsadat Mireshghallah, Archit Uniyal, Tianhao Wang, David Evans, Taylor Berg-Kirkpatrick

ICLR 2022 What Happens After SGD Reaches Zero Loss? --a Mathematical Framework Zhiyuan Li, Tianhao Wang, Sanjeev Arora

AAAI 2021 Improving Robustness to Model Inversion Attacks via Mutual Information Regularization Tianhao Wang, Yuheng Zhang, Ruoxi Jia

NeurIPS 2021 Provably Efficient Reinforcement Learning with Linear Function Approximation Under Adaptivity Constraints Tianhao Wang, Dongruo Zhou, Quanquan Gu

NeurIPS 2021 Variance-Aware Off-Policy Evaluation with Linear Function Approximation Yifei Min, Tianhao Wang, Dongruo Zhou, Quanquan Gu

AISTATS 2018 Accelerated Stochastic Mirror Descent: From Continuous-Time Dynamics to Discrete-Time Algorithms Pan Xu, Tianhao Wang, Quanquan Gu

ICML 2018 Continuous and Discrete-Time Accelerated Stochastic Mirror Descent for Strongly Convex Functions Pan Xu, Tianhao Wang, Quanquan Gu