Search Results for author: Jingbin Wang

Found 8 papers, 0 papers with code

LDCCNLP at IJCNLP-2017 Task 2: Dimensional Sentiment Analysis for Chinese Phrases Using Machine Learning

no code implementations IJCNLP 2017 Peng Zhong, Jingbin Wang

In our system, the MAE predictive values of Valence and Arousal were 0. 811 and 0. 996, respectively, for the sentiment dimension prediction of words in Chinese.

BIG-bench Machine Learning Sentiment Analysis +1

A novel image tag completion method based on convolutional neural network

no code implementations2 Mar 2017 Yanyan Geng, Guohui Zhang, Weizhi Li, Yi Gu, Ru-Ze Liang, Gaoyuan Liang, Jingbin Wang, Yanbin Wu, Nitin Patil, Jing-Yan Wang

In this paper, we study the problem of image tag complete and proposed a novel method for this problem based on a popular image representation method, convolutional neural network (CNN).

Image Retrieval Retrieval +1

Learning convolutional neural network to maximize Pos@Top performance measure

no code implementations27 Sep 2016 Yanyan Geng, Ru-Ze Liang, Weizhi Li, Jingbin Wang, Gaoyuan Liang, Chenhao Xu, Jing-Yan Wang

The CNN model is used to represent the multi-instance data point, and a classifier function is used to predict the label from the its CNN representation.

BIG-bench Machine Learning POS

Semi-supervised structured output prediction by local linear regression and sub-gradient descent

no code implementations7 Jun 2016 Ru-Ze Liang, Wei Xie, Weizhi Li, Xin Du, Jim Jing-Yan Wang, Jingbin Wang

The existing semi-supervise structured output prediction methods learn a global predictor for all the data points in a data set, which ignores the differences of local distributions of the data set, and the effects to the structured output prediction.

regression Structured Prediction

Multiple kernel multivariate performance learning using cutting plane algorithm

no code implementations25 Aug 2015 Jingbin Wang, Haoxiang Wang, Yihua Zhou, Nancy McDonald

The learning of the classifier parameter and the kernel weight are unified in a single objective function considering to minimize the upper boundary of the given multivariate performance measure.

General Classification

Supervised learning of sparse context reconstruction coefficients for data representation and classification

no code implementations18 Aug 2015 Xuejie Liu, Jingbin Wang, Ming Yin, Benjamin Edwards, Peijuan Xu

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.

Classification General Classification

Vector Quantization by Minimizing Kullback-Leibler Divergence

no code implementations30 Jan 2015 Lan Yang, Jingbin Wang, Yujin Tu, Prarthana Mahapatra, Nelson Cardoso

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 original vectors, and the output, which is the quantization subsets of the vector set.

General Classification Image Classification +1

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