21 citations · 22 across the 3 of their papers we have counts for
4 papers · 1 filter
Nonconvex Stochastic Scaled-Gradient Descent and Generalized Eigenvector Problems
Chris Junchi Li, Michael I. Jordan
Motivated by the problem of online canonical correlation analysis, we propose the \emph{Stochastic Scaled-Gradient Descent} (SSGD) algorithm for minimizing the expectation of a sto…
On Linear Stochastic Approximation: Fine-grained Polyak-Ruppert and Non-Asymptotic Concentration
Wenlong Mou, Chris Junchi Li, Martin J. Wainwright +2
We undertake a precise study of the asymptotic and non-asymptotic properties of stochastic approximation procedures with Polyak-Ruppert averaging for solving a linear system $\bar{…
Diffusion Approximations for Online Principal Component Estimation and Global Convergence
Chris Junchi Li, Mengdi Wang, Han Liu +1
In this paper, we propose to adopt the diffusion approximation tools to study the dynamics of Oja's iteration which is an online stochastic gradient descent method for the principa…
Online ICA: Understanding Global Dynamics of Nonconvex Optimization via Diffusion Processes
Chris Junchi Li, Zhaoran Wang, Han Liu
Solving statistical learning problems often involves nonconvex optimization. Despite the empirical success of nonconvex statistical optimization methods, their global dynamics, esp…