(Following conventions of math and theoretical computer science, authors are listed in alphabetical order.)

Minimum Cut is More Efficient than Sparsification in a Stream.
with Matthew Ding, Jason Li, Jelani Nelson, and David P. Woodruff

Optimal Sketching for Residual Error Estimation for Matrix and Vector Norms.
with Yi Li and David P. Woodruff
ICLR 2024

Tight Lower Bounds for Directed Cut Sparsification and Distributed Min-Cut.
with Yu Cheng, Max Li, Zi-Yi Tai, David P. Woodruff, and Jason Zhang
PODS 2024

$\ell_p$-Regression in the Arbitrary Partition Model of Communication.
with Yi Li and David P. Woodruff
COLT 2023

Learning the Positions in CountSketch.
with Yi Li, Simin Liu, Ali Vakilian, and David P. Woodruff
ICLR 2023 (spotlight)

The $\ell_p$-Subspace Sketch Problem in Small Dimensions with Applications to Support Vector Machines.
with Yi Li and David P. Woodruff
SODA 2023

Streaming Algorithms with Large Approximation Factors.
with Yi Li, David P. Woodruff, and Yuheng Zhang

Learning-Augmented Binary Search Trees.
with Tian Luo, and David P. Woodruff
ICML 2022

Quantum-Inspired Algorithms from Randomized Numerical Linear Algebra.
with Nadiia Chepurko, Kenneth L. Clarkson, Lior Horesh, and David P. Woodruff
ICML 2022

Triangle and Four-Cycle Counting with Predictions in Graph Stream.
with Justin Chen, Talya Eden, Piotr Indyk, Shyam Narayanan, Ronitt Rubinfeld, Sandeep Silwal, Tal Wagner,
David P. Woodruff, and Michael Zhang
ICLR 2022

Robust Learning of Fixed-Structure Bayesian Networks in Nearly-Linear Time.
with Yu Cheng
ICLR 2021

Learning-Augmented Data Stream Algorithms.
with Tanqiu Jiang, Yi Li, Yisong Ruan, and David P. Woodruff
ICLR 2020