163 citations · 1.6k across the 92 of their papers we have counts for
10 papers · 1 filter
Analysis of Distributed Stochastic Dual Coordinate Ascent
Tianbao Yang, Shenghuo Zhu, Rong Jin +1
In \citep{Yangnips13}, the author presented distributed stochastic dual coordinate ascent (DisDCA) algorithms for solving large-scale regularized loss minimization. Extraordinary p…
Stochastic Optimization of Smooth Loss
Rong Jin
In this paper, we first prove a high probability bound rather than an expectation bound for stochastic optimization with smooth loss. Furthermore, the existing analysis requires th…
Beating the Minimax Rate of Active Learning with Prior Knowledge
Lijun Zhang, Mehrdad Mahdavi, Rong Jin
Active learning refers to the learning protocol where the learner is allowed to choose a subset of instances for labeling. Previous studies have shown that, compared with passive l…
MixedGrad: An O(1/T) Convergence Rate Algorithm for Stochastic Smooth Optimization
Mehrdad Mahdavi, Rong Jin
It is well known that the optimal convergence rate for stochastic optimization of smooth functions is , which is same as stochastic optimization of Lipschitz continu…
A Random Matrix Approach to Differential Privacy and Structure Preserved Social Network Graph Publishing
Faraz Ahmed, Rong Jin, Alex X. Liu
Online social networks are being increasingly used for analyzing various societal phenomena such as epidemiology, information dissemination, marketing and sentiment flow. Popular a…
One-Pass AUC Optimization
Wei Gao, Rong Jin, Shenghuo Zhu +1
AUC is an important performance measure and many algorithms have been devoted to AUC optimization, mostly by minimizing a surrogate convex loss on a training data set. In this work…