Liu, Xiyang

11 publications

COLT 2024 Insufficient Statistics Perturbation: Stable Estimators for Private Least Squares Extended Abstract Gavin Brown, Jonathan Hayase, Samuel Hopkins, Weihao Kong, Xiyang Liu, Sewoong Oh, Juan C Perdomo, Adam Smith

NeurIPS 2023 Hierarchical Vector Quantized Transformer for Multi-Class Unsupervised Anomaly Detection Ruiying Lu, YuJie Wu, Long Tian, Dongsheng Wang, Bo Chen, Xiyang Liu, Ruimin Hu

NeurIPS 2023 Label Robust and Differentially Private Linear Regression: Computational and Statistical Efficiency Xiyang Liu, Prateek Jain, Weihao Kong, Sewoong Oh, Arun Suggala

ICCV 2023 Prototypes-Oriented Transductive Few-Shot Learning with Conditional Transport Long Tian, Jingyi Feng, Xiaoqiang Chai, Wenchao Chen, Liming Wang, Xiyang Liu, Bo Chen

NeurIPS 2022 DP-PCA: Statistically Optimal and Differentially Private PCA Xiyang Liu, Weihao Kong, Prateek Jain, Sewoong Oh

COLT 2022 Differential Privacy and Robust Statistics in High Dimensions Xiyang Liu, Weihao Kong, Sewoong Oh

TMLR 2022 Mace: A Flexible Framework for Membership Privacy Estimation in Generative Models Yixi Xu, Sumit Mukherjee, Xiyang Liu, Shruti Tople, Rahul M Dodhia, Juan M Lavista Ferres

ICML 2021 KO Codes: Inventing Nonlinear Encoding and Decoding for Reliable Wireless Communication via Deep-Learning Ashok V Makkuva, Xiyang Liu, Mohammad Vahid Jamali, Hessam Mahdavifar, Sewoong Oh, Pramod Viswanath

NeurIPS 2021 Robust and Differentially Private Mean Estimation Xiyang Liu, Weihao Kong, Sham Kakade, Sewoong Oh

ECCV 2020 Adaptive Mixture Regression Network with Local Counting mAP for Crowd Counting Xiyang Liu, Jie Yang, Wenrui Ding, Tieqiang Wang, Zhijin Wang, Junjun Xiong

NeurIPS 2019 Minimax Optimal Estimation of Approximate Differential Privacy on Neighboring Databases Xiyang Liu, Sewoong Oh