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A Minibatch Proximal Stochastic Recursive Gradient Algorithm Using a Trust-Region-Like Scheme and Barzilai-Borwein Stepsizes 期刊论文
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, 2021, 卷号: 32, 期号: 10, 页码: 4627-4638
作者:  Yu, Tengteng;  Liu, Xin-Wei;  Dai, Yu-Hong;  Sun, Jie
收藏  |  浏览/下载：123/0  |  提交时间：2022/04/02
Convergence  Convex functions  Risk management  Gradient methods  Learning systems  Sun  Barzilai-Borwein (BB) method  empirical risk minimization (ERM)  proximal method  stochastic gradient  trust-region  
One-Shot Neural Architecture Search: Maximising Diversity to Overcome Catastrophic Forgetting 期刊论文
IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, 2021, 卷号: 43, 期号: 9, 页码: 2921-2935
作者:  Zhang, Miao;  Li, Huiqi;  Pan, Shirui;  Chang, Xiaojun;  Zhou, Chuan;  Ge, Zongyuan;  Su, Steven
收藏  |  浏览/下载：167/0  |  提交时间：2021/10/26
Computer architecture  Training  Optimization  Neural networks  Search methods  Australia  Germanium  AutoML  neural architecture search  continual learning  catastrophic forgetting  novelty search  
A Minimax Probability Machine for Nondecomposable Performance Measures 期刊论文
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, 2021, 页码: 13
作者:  Luo, Junru;  Qiao, Hong;  Zhang, Bo
收藏  |  浏览/下载：146/0  |  提交时间：2022/04/02
Measurement  Task analysis  Covariance matrices  Support vector machines  Prediction algorithms  Minimization  Kernel  Imbalanced classification  minimax probability machine  nondecomposable performance measures  
Clustering Hidden Markov Models With Variational Bayesian Hierarchical EM 期刊论文
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, 2021, 页码: 15
作者:  Lan, Hui;  Liu, Ziquan;  Hsiao, Janet H.;  Yu, Dan;  Chan, Antoni B.
收藏  |  浏览/下载：164/0  |  提交时间：2022/04/02
Hidden Markov models  Bayes methods  Data models  Computational modeling  Mixture models  Clustering algorithms  Analytical models  Clustering  hidden Markov mixture model (H3M)  hierarchical EM  variational Bayesian (VB)  
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：162/0  |  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  
Observer-Based Output Feedback Event-Triggered Adaptive Control for Linear Multiagent Systems Under Switching Topologies 期刊论文
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, 2021, 页码: 11
作者:  Zhang, Juan;  Zhang, Huaguang;  Zhang, Kun;  Cai, Yuliang
收藏  |  浏览/下载：116/0  |  提交时间：2022/04/02
Topology  Protocols  Synchronization  Switches  Consensus control  Output feedback  Adaptive control  Adaptive control  event-triggered control  output feedback control  switching topologies  
Deep Nitsche Method: Deep Ritz Method with Essential Boundary Conditions 期刊论文
COMMUNICATIONS IN COMPUTATIONAL PHYSICS, 2021, 卷号: 29, 期号: 5, 页码: 1365-1384
作者:  Liao, Yulei;  Ming, Pingbing
收藏  |  浏览/下载：157/0  |  提交时间：2021/06/01
Deep Nitsche Method  Deep Ritz Method  neural network approximation  mixed boundary conditions  curse of dimensionality  
A Novel Synchronization Protocol for Nonlinear Stochastic Dynamical Networked Systems 期刊论文
IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS, 2021, 卷号: 51, 期号: 5, 页码: 2676-2686
作者:  Gu, Haibo;  Wang, Xiong;  Liu, Kexin;  Lu, Jinhu
收藏  |  浏览/下载：181/0  |  提交时间：2021/06/01
Synchronization  Protocols  Stochastic processes  Artificial neural networks  Adaptive systems  Perturbation methods  Complex dynamical network  Lyapunov function  networked system  stochastic perturbation  synchronization  
Anomaly Detection on Attributed Networks via Contrastive Self-Supervised Learning 期刊论文
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, 2021, 页码: 15
作者:  Liu, Yixin;  Li, Zhao;  Pan, Shirui;  Gong, Chen;  Zhou, Chuan;  Karypis, George
收藏  |  浏览/下载：122/0  |  提交时间：2022/04/02
Anomaly detection  Task analysis  Graph neural networks  Unsupervised learning  Predictive models  Pattern matching  Training  Anomaly detection  attributed networks  contrastive self-supervised learning  graph neural networks (GNNs)  unsupervised learning  
Learning nonlinear operators via DeepONet based on the universal approximation theorem of operators 期刊论文
NATURE MACHINE INTELLIGENCE, 2021, 卷号: 3, 期号: 3, 页码: 218-+
作者:  Lu, Lu;  Jin, Pengzhan;  Pang, Guofei;  Zhang, Zhongqiang;  Karniadakis, George Em
收藏  |  浏览/下载：207/0  |  提交时间：2021/06/01