339 citations · 1k across the 41 of their papers we have counts for
6 papers · 1 filter
Online Stochastic Optimization with Multiple Objectives
Mehrdad Mahdavi, Tianbao Yang, Rong Jin
In this paper we propose a general framework to characterize and solve the stochastic optimization problems with multiple objectives underlying many real world learning application…
Recovering the Optimal Solution by Dual Random Projection
Lijun Zhang, Mehrdad Mahdavi, Rong Jin +2
Random projection has been widely used in data classification. It maps high-dimensional data into a low-dimensional subspace in order to reduce the computational cost in solving th…
An Improved Bound for the Nystrom Method for Large Eigengap
Mehrdad Mahdavi, Tianbao Yang, Rong Jin
We develop an improved bound for the approximation error of the Nyström method under the assumption that there is a large eigengap in the spectrum of kernel matrix. This is based o…
Multiple Kernel Learning from Noisy Labels by Stochastic Programming
Tianbao Yang, Mehrdad Mahdavi, Rong Jin +2
We study the problem of multiple kernel learning from noisy labels. This is in contrast to most of the previous studies on multiple kernel learning that mainly focus on developing…
Efficient Constrained Regret Minimization
Mehrdad Mahdavi, Tianbao Yang, Rong Jin
Online learning constitutes a mathematical and compelling framework to analyze sequential decision making problems in adversarial environments. The learner repeatedly chooses an ac…
An Efficient Primal-Dual Prox Method for Non-Smooth Optimization
Tianbao Yang, Mehrdad Mahdavi, Rong Jin +1
We study the non-smooth optimization problems in machine learning, where both the loss function and the regularizer are non-smooth functions. Previous studies on efficient empirica…