1 citations · 1 across the 6 of their papers we have counts for
6 papers
OneShot: Index-in-Ranking with Neural Scoring for Large-Scale Retrieval
Ziwei Li, Shuyao Li, Xufeng Cai +12
In modern recommendation systems, retrieval serves as a primary stage responsible for filtering billions of candidate items down to thousands prior to refined ranking. To make this…
Robust Learning of a Group DRO Neuron
Guyang Cao, Shuyao Li, Sushrut Karmalkar +1
We study the problem of learning a single neuron under standard squared loss in the presence of arbitrary label noise and group-level distributional shifts, for a broad family of c…
Distributionally Robust Optimization with Adversarial Data Contamination
Shuyao Li, Ilias Diakonikolas, Jelena Diakonikolas
Distributionally Robust Optimization (DRO) provides a framework for decision-making under distributional uncertainty, yet its effectiveness can be compromised by outliers in the tr…
Learning a Single Neuron Robustly to Distributional Shifts and Adversarial Label Noise
Shuyao Li, Sushrut Karmalkar, Ilias Diakonikolas +1
We study the problem of learning a single neuron with respect to the -loss in the presence of adversarial distribution shifts, where the labels can be arbitrary, and the goa…
Robust Second-Order Nonconvex Optimization and Its Application to Low Rank Matrix Sensing
Shuyao Li, Yu Cheng, Ilias Diakonikolas +3
Finding an approximate second-order stationary point (SOSP) is a well-studied and fundamental problem in stochastic nonconvex optimization with many applications in machine learnin…
A randomized algorithm for nonconvex minimization with inexact evaluations and complexity guarantees
Shuyao Li, Stephen J. Wright
We consider minimization of a smooth nonconvex function with inexact oracle access to gradient and Hessian (without assuming access to the function value) to achieve approximate se…