95 citations · 127 across the 6 of their papers we have counts for
6 papers
Semi-supervised structured output prediction by local linear regression and sub-gradient descent
Ru-Ze Liang, Wei Xie, Weizhi Li +3
We propose a novel semi-supervised structured output prediction method based on local linear regression in this paper. The existing semi-supervise structured output prediction meth…
Multiple kernel multivariate performance learning using cutting plane algorithm
Jingbin Wang, Haoxiang Wang, Yihua Zhou +1
In this paper, we propose a multi-kernel classifier learning algorithm to optimize a given nonlinear and nonsmoonth multivariate classifier performance measure. Moreover, to solve…
Supervised learning of sparse context reconstruction coefficients for data representation and classification
Xuejie Liu, Jingbin Wang, Ming Yin +2
Context of data points, which is usually defined as the other data points in a data set, has been found to play important roles in data representation and classification. In this p…
Supervised cross-modal factor analysis for multiple modal data classification
Jingbin Wang, Yihua Zhou, Kanghong Duan +2
In this paper we study the problem of learning from multiple modal data for purpose of document classification. In this problem, each document is composed two different modals of d…
Vector Quantization by Minimizing Kullback-Leibler Divergence
Lan Yang, Jingbin Wang, Yujin Tu +2
This paper proposes a new method for vector quantization by minimizing the Kullback-Leibler Divergence between the class label distributions over the quantization inputs, which are…
Learning Fine-grained Image Similarity with Deep Ranking
Jiang Wang, Yang song, Thomas Leung +5
Learning fine-grained image similarity is a challenging task. It needs to capture between-class and within-class image differences. This paper proposes a deep ranking model that em…