1 citations · 1 across the 5 of their papers we have counts for
5 papers
Computation of Strong Solutions to Stochastic Variational Inequalities
Yao Ji, Guanghui Lan, Jason Zhu
This paper studies the computation of strong solutions of monotone variational inequalities (VIs) with Lipschitz continuous operators. Building on the idea of accumulative regulari…
Stochastic Auto-conditioned Fast Gradient Methods with Optimal Rates
Yao Ji, Guanghui Lan
Achieving optimal rates for stochastic composite convex optimization without prior knowledge of problem parameters remains a central challenge. In the deterministic setting, the au…
High-order Accumulative Regularization for Gradient Minimization in Convex Programming
Yao Ji, Guanghui Lan
This paper develops a unified high-order accumulative regularization (AR) framework for convex and uniformly convex gradient norm minimization. Existing high-order methods often ex…
GRIT: Out-of-Distribution Robustness from Finite and Noisy Invariant Pairs
Ruqi Bai, Yao Ji, Easton Currie +3
Predictors often exploit spurious correlations that fail under distribution shift, undermining out-of-distribution (OOD) robustness. Invariant pairs, such as the same object photog…
Distributed Sparse Regression via Penalization
Yao Ji, Gesualdo Scutari, Ying Sun +1
We study sparse linear regression over a network of agents, modeled as an undirected graph (with no centralized node). The estimation problem is formulated as the minimization of t…