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Disentangled Text Representation Learning With Information-Theoretic Perspective for Adversarial Robustness 期刊论文
IEEE-ACM TRANSACTIONS ON AUDIO SPEECH AND LANGUAGE PROCESSING, 2024, 卷号: 32, 页码: 1237-1247
作者:  Zhao, Jiahao;  Mao, Wenji;  Zeng, Daniel Dajun
收藏  |  浏览/下载：7/0  |  提交时间：2024/07/03
Adversarial robustness  variation of information  disentangled text representation learning  
A deep latent space model for interpretable representation learning on directed graphs 期刊论文
NEUROCOMPUTING, 2024, 卷号: 576, 页码: 13
作者:  Yang, Hanxuan;  Kong, Qingchao;  Mao, Wenji
收藏  |  浏览/下载：28/0  |  提交时间：2024/05/30
Graph representation learning  Deep latent space model  Model interpretability  Variational auto-encoder  Directed graph  
Learning Dynamic Dependencies With Graph Evolution Recurrent Unit for Stock Predictions 期刊论文
IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS, 2023, 页码: 13
作者:  Tian, Hu;  Zhang, Xingwei;  Zheng, Xiaolong;  Zeng, Daniel Dajun
收藏  |  浏览/下载：85/0  |  提交时间：2023/11/17
Gated recurrent unit  graph representation learning  learning dynamic dependencies  stock prediction system  
An Orthogonal Subspace Decomposition Method for Cross-Modal Retrieval 期刊论文
IEEE INTELLIGENT SYSTEMS, 2022, 卷号: 37, 期号: 3, 页码: 45-53
作者:  Zeng, Zhixiong;  Xu, Nan;  Mao, Wenji;  Zeng, Daniel
Adobe PDF(2545Kb)  |  收藏  |  浏览/下载：351/52  |  提交时间：2022/09/19
Semantics  Representation learning  Task analysis  Matrix decomposition  Automation  Interference  Intelligent systems  Cross-modal Retrieval  Representation Learning  Orthogonal Decomposition  
Inductive Representation Learning on Dynamic Stock Co-Movement Graphs for Stock Predictions 期刊论文
INFORMS JOURNAL ON COMPUTING, 2022, 页码: 19
作者:  Tian, Hu;  Zheng, Xiaolong;  Zhao, Kang;  Liu, Maggie Wenjing;  Zeng, Daniel Dajun
Adobe PDF(1329Kb)  |  收藏  |  浏览/下载：350/80  |  提交时间：2022/07/25
graph representation learning  deep learning  predictive models  business intelligence  
Deep Neural Network Self-Distillation Exploiting Data Representation Invariance 期刊论文
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, 2022, 卷号: 33, 期号: 1, 页码: 257-269
作者:  Xu, Ting-Bing;  Liu, Cheng-Lin
收藏  |  浏览/下载：211/0  |  提交时间：2022/02/16
Training  Nonlinear distortion  Data models  Neural networks  Knowledge engineering  Network architecture  Generalization error  network compression  representation invariance  self-distillation (SD)