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Qingcheng Fan, Sicong Liu, Chunjiang Zhao and Shuqin Li
Feature selection is crucial in classification tasks as it helps to extract relevant information while reducing redundancy. This paper presents a novel method that considers both instance and label correlation. By employing the least squares method, we c...
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Charalampos M. Liapis and Sotiris Kotsiantis
The use of deep learning in conjunction with models that extract emotion-related information from texts to predict financial time series is based on the assumption that what is said about a stock is correlated with the way that stock fluctuates. Given th...
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Wenbin Zheng, Jinjin Li and Shujiao Liao
Multi-label learning has become a hot topic in recent years, attracting scholars? attention, including applying the rough set model in multi-label learning. Exciting works that apply the rough set model into multi-label learning usually adapt the rough s...
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Jun Huang, Qian Xu, Xiwen Qu, Yaojin Lin and Xiao Zheng
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Jiyue Wang, Pei Zhang, Qianhua He, Yanxiong Li and Yongjian Hu
Label Smoothing Regularization (LSR) is a widely used tool to generalize classification models by replacing the one-hot ground truth with smoothed labels. Recent research on LSR has increasingly focused on the correlation between the LSR and Knowledge Di...
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Kai-Sheng Chen
We present packet switching applications based on extended spectral-amplitude-coding (SAC) labels in generalized multi-protocol label switching (GMPLS) networks. The proposed approach combines the advantages of wavelength-division multiplexing (WDM) and ...
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Xiangpeng Song, Hongbin Yang and Congcong Zhou
Pedestrian attribute recognition is to predict a set of attribute labels of the pedestrian from surveillance scenarios, which is a very challenging task for computer vision due to poor image quality, continual appearance variations, as well as diverse sp...
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Wenkuan Li, Peiyu Liu, Qiuyue Zhang and Wenfeng Liu
Text sentiment analysis is an important but challenging task. Remarkable success has been achieved along with the wide application of deep learning methods, but deep learning methods dealing with text sentiment classification tasks cannot fully exploit s...
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