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Structure-Aware Prototypical Neural Process for Few-Shot Graph Classification 期刊论文
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, 2022, 页码: 15
作者:  Lin, Xixun;  Li, Zhao;  Zhang, Peng;  Liu, Luchen;  Zhou, Chuan;  Wang, Bin;  Tian, Zhihong
收藏  |  浏览/下载：99/0  |  提交时间：2023/02/07
Task analysis  Kernel  Training  Decoding  Stochastic processes  Predictive models  Computational modeling  Few-shot learning  graph classification  graph neural networks (GNNs)  neural process (NP)  
A Comprehensive Survey on Community Detection With Deep Learning 期刊论文
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, 2022, 页码: 21
作者:  Su, Xing;  Xue, Shan;  Liu, Fanzhen;  Wu, Jia;  Yang, Jian;  Zhou, Chuan;  Hu, Wenbin;  Paris, Cecile;  Nepal, Surya;  Jin, Di;  Sheng, Quan Z.;  Yu, Philip S.
收藏  |  浏览/下载：142/0  |  提交时间：2022/04/29
Deep learning  Taxonomy  Optimization  Partitioning algorithms  Clustering algorithms  Social networking (online)  Peer-to-peer computing  Community detection  deep learning  graph neural network  network representation  social networks  
Online Active Learning for Drifting Data Streams 期刊论文
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, 2021, 页码: 15
作者:  Liu, Sanmin;  Xue, Shan;  Wu, Jia;  Zhou, Chuan;  Yang, Jian;  Li, Zhao;  Cao, Jie
收藏  |  浏览/下载：141/0  |  提交时间：2022/04/02
Labeling  Data models  Uncertainty  Biological system modeling  Computational modeling  Cognition  Adaptation models  Active learning  concept drift  data stream classification  online incremental learning  
Circular Complex-Valued GMDH-Type Neural Network for Real-Valued Classification Problems 期刊论文
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, 2020, 卷号: 31, 期号: 12, 页码: 5285-5299
作者:  Xiao, Jin;  Jia, Yanlin;  Jiang, Xiaoyi;  Wang, Shouyang
收藏  |  浏览/下载：133/0  |  提交时间：2021/04/26
Biological system modeling  Data models  Biological neural networks  Predictive models  Neurons  Mathematical model  Complex-valued external criterion  complex-valued group method of data handling (GMDH)-type neural network  parameter estimation  real-valued classification  
Robust Novelty Detection via Worst Case CVaR Minimization 期刊论文
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, 2015, 卷号: 26, 期号: 9, 页码: 2098-2110
作者:  Wang, Yongqiao;  Dang, Chuangyin;  Wang, Shouyang
收藏  |  浏览/下载：114/0  |  提交时间：2018/07/30
Conditional value-at-risk (CVaR)  kernel methods  novelty detection  robust programming  single-class support vector machine (SSVM)