most citedLearning manifold to regularize nonnegative matrix factorization

2 citations · 2 across the 6 of their papers we have counts for

collaborators

6 papers

cs.LG2015

Regularized maximum correntropy machine

Jim Jing-Yan Wang, Yunji Wang, Bing-Yi Jing +1

In this paper we investigate the usage of regularized correntropy framework for learning of classifiers from noisy labels. The class label predictors learned by minimizing transiti…

cs.LG2015

Multi-view learning for multivariate performance measures optimization

Jim Jing-Yan Wang

In this paper, we propose the problem of optimizing multivariate performance measures from multi-view data, and an effective method to solve it. This problem has two features: the…

cs.LG20142 cited

Learning manifold to regularize nonnegative matrix factorization

Jim Jing-Yan Wang, Xin Gao

Inthischapterwediscusshowtolearnanoptimalmanifoldpresentationto regularize nonegative matrix factorization (NMF) for data representation problems. NMF,whichtriestorepresentanonnega…

cs.LG2014

Maximum mutual information regularized classification

Jim Jing-Yan Wang, Yi Wang, Shiguang Zhao +1

In this paper, a novel pattern classification approach is proposed by regularizing the classifier learning to maximize mutual information between the classification response and th…

cs.LG2014

Domain Transfer Structured Output Learning

Jim Jing-Yan Wang

In this paper, we propose the problem of domain transfer structured output learn- ing and the first solution to solve it. The problem is defined on two different data domains shari…

cs.OH2014

An Efficient Topology-Based Algorithm for Transient Analysis of Power Grid

Jim Jing-Yan Wang, Lan Yang, Jingbin Wang +1

In the design flow of integrated circuits, chip-level verification is an important step that sanity checks the performance is as expected. Power grid verification is one of the mos…