most citedFast Bounded Online Gradient Descent Algorithms for Scalable Kernel-Based Online Learning

41 citations · 80 across the 5 of their papers we have counts for

collaborators

5 papers

cs.LG201214 cited

A Simple Algorithm for Semi-supervised Learning with Improved Generalization Error Bound

Ming Ji, Tianbao Yang, Binbin Lin +2

In this work, we develop a simple algorithm for semi-supervised regression. The key idea is to use the top eigenfunctions of integral operator derived from both labeled and unlabel…

cs.LG201241 cited

Fast Bounded Online Gradient Descent Algorithms for Scalable Kernel-Based Online Learning

Peilin Zhao, Jialei Wang, Pengcheng Wu +2

Kernel-based online learning has often shown state-of-the-art performance for many online learning tasks. It, however, suffers from a major shortcoming, that is, the unbounded numb…

cs.LG201213 cited

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…

cs.SI20124 cited

A Bayesian Framework for Community Detection Integrating Content and Link

Tianbao Yang, Rong Jin, Yun Chi +1

This paper addresses the problem of community detection in networked data that combines link and content analysis. Most existing work combines link and content information by a gen…

cs.LG20128 cited

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…