Ph.D. Student
Paul G.Allen School of Computer Science & Engineering
University of Washington
xiyangl at cs dot washington dot edu
I am currently a Ph.D. student in CS department at University of Washington, advised by Sewoong Oh. Previously, I received my M.S. and B.Eng. in Electrical Engineering from University of Illinois at Urbana-Champaign and Shanghai Jiao Tong University，respectively. My research has been supported by the 2021 Qualcomm innovation fellowship.
My research interests include deep learning, robust statistics, and differential privacy.
*Equal contributions
Insufficient Statistics Perturbation: Stable Estimators for Private Least Squares
Gavin Brown, Jonathan Hayase, Samuel Hopkins, Weihao Kong, Xiyang Liu, Sewoong Oh, Juan C. Perdomo, Adam Smith
COLT 2024
Label Robust and Differentially Private Linear Regression: Computational and Statistical Efficiency
Xiyang Liu, Prateek Jain, Weihao Kong, Sewoong Oh, Arun Sai Suggala
NeurIPS 2023
DP-PCA: Statistically Optimal and Differentially Private PCA
Xiyang Liu, Weihao Kong, Prateek Jain, Sewoong Oh
NeurIPS 2022
Differential Privacy and Robust Statistics in High Dimensions
Xiyang Liu, Weihao Kong, Sewoong Oh
COLT 2022; [Spotlight talk at PPAI’22 workshop]
Reconstruction of visual images from mouse retinal ganglion cell spiking activity using convolutional neural networks
Tyler Benster, Darwin Babino, John Thickstun, Matthew Hunt, Xiyang Liu, Zaid Harchaoui, Sewoong Oh, Russell N. Van Gelder
bioRxiv
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
Transactions on Machine Learning Research (TMLR)
Robust and Differentially Private Mean Estimation
Xiyang Liu, Weihao Kong, Sham Kakade, Sewoong Oh
NeurIPS 2021; [talk by Sewoong at Simons Institute][talk at FL-ICML’21 workshop(starting from 45 minutes)]
KO codes: Inventing Nonlinear Encoding and Decoding for Reliable Wireless Communication via Deep-Learning
Ashok Vardhan Makkuva*, Xiyang Liu*, Mohammad Vahid Jamali, Hessam Mahdavifar, Sewoong Oh, Pramod Viswanath
ICML 2021; [code][talk by Hessam]
Reed-Muller Subcodes: Machine Learning-Aided Design of Efficient Soft Recursive Decoding
Mohammad Vahid Jamali, Xiyang Liu, Ashok Vardhan Makkuva, Hessam Mahdavifar, Sewoong Oh, Pramod Viswanath
ISIT 2021
Minimax Rates of Estimating Approximate Differential Privacy
Xiyang Liu, Sewoong Oh
NeurIPS 2019; [code][application in PyDP library integrated by OpenMined]
Graph Matching by Graph Neural Network