Chang, Xiangyu

16 publications

CVPR 2025 AdMiT: Adaptive Multi-Source Tuning in Dynamic Environments Xiangyu Chang, Fahim Faisal Niloy, Sk Miraj Ahmed, Srikanth V. Krishnamurthy, Basak Guler, Ananthram Swami, Samet Oymak, Amit Roy-Chowdhury

ICLR 2025 ProAdvPrompter: A Two-Stage Journey to Effective Adversarial Prompting for LLMs Hao Di, Tong He, Haishan Ye, Yinghui Huang, Xiangyu Chang, Guang Dai, Ivor Tsang

AISTATS 2025 Provable Benefits of Task-Specific Prompts for In-Context Learning Xiangyu Chang, Yingcong Li, Muti Kara, Samet Oymak, Amit Roy-Chowdhury

NeurIPS 2025 When and How Unlabeled Data Provably Improve In-Context Learning Yingcong Li, Xiangyu Chang, Muti Kara, Xiaofeng Liu, Amit Roy-Chowdhury, Samet Oymak

NeurIPS 2024 CONTRAST: Continual Multi-Source Adaptation to Dynamic Distributions Sk Miraj Ahmed, Fahim Faisal Niloy, Xiangyu Chang, Dripta S. Raychaudhuri, Samet Oymak, Amit K. Roy-Chowdhury

ICML 2024 Double Stochasticity Gazes Faster: Snap-Shot Decentralized Stochastic Gradient Tracking Methods Hao Di, Haishan Ye, Xiangyu Chang, Guang Dai, Ivor Tsang

ICML 2024 Double Variance Reduction: A Smoothing Trick for Composite Optimization Problems Without First-Order Gradient Hao Di, Haishan Ye, Yueling Zhang, Xiangyu Chang, Guang Dai, Ivor Tsang

MLJ 2024 Fedpower: Privacy-Preserving Distributed Eigenspace Estimation Xiao Guo, Xiang Li, Xiangyu Chang, Shusen Wang, Zhihua Zhang

NeurIPS 2024 Selective Attention: Enhancing Transformer Through Principled Context Control Xuechen Zhang, Xiangyu Chang, Mingchen Li, Amit Roy-Chowdhury, Jiasi Chen, Samet Oymak

ICML 2023 2D-Shapley: A Framework for Fragmented Data Valuation Zhihong Liu, Hoang Anh Just, Xiangyu Chang, Xi Chen, Ruoxi Jia

NeurIPSW 2023 Augmenting Federated Learning with Pretrained Transformers Xuechen Zhang, Mingchen Li, Xiangyu Chang, Jiasi Chen, Amit Roy-Chowdhury, Ananda Suresh, Samet Oymak

JMLR 2023 Randomized Spectral Co-Clustering for Large-Scale Directed Networks Xiao Guo, Yixuan Qiu, Hai Zhang, Xiangyu Chang

COLT 2022 Statistical Estimation and Online Inference via Local SGD Xiang Li, Jiadong Liang, Xiangyu Chang, Zhihua Zhang

AAAI 2021 Provable Benefits of Overparameterization in Model Compression: From Double Descent to Pruning Neural Networks Xiangyu Chang, Yingcong Li, Samet Oymak, Christos Thrampoulidis

AAAI 2018 Predicting Depression Severity by Multi-Modal Feature Engineering and Fusion Aven Samareh, Yan Jin, Zhangyang Wang, Xiangyu Chang, Shuai Huang

JMLR 2017 Distributed Semi-Supervised Learning with Kernel Ridge Regression Xiangyu Chang, Shao-Bo Lin, Ding-Xuan Zhou