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Data-driven peakon and periodic peakon solutions and parameter discovery of some nonlinear dispersive equations via deep learning 期刊论文
PHYSICA D-NONLINEAR PHENOMENA, 2021, 卷号: 428, 页码: 15
作者:  Wang, Li;  Yan, Zhenya
收藏  |  浏览/下载：116/0  |  提交时间：2022/04/02
Nonlinear dispersive equation  Initial-boundary value conditions  Physics-informed neural networks  Deep learning  Data-driven peakon and periodic peakon  solutions Data-driven parameter discovery  
OnsagerNet: Learning stable and interpretable dynamics using a generalized Onsager principle 期刊论文
PHYSICAL REVIEW FLUIDS, 2021, 卷号: 6, 期号: 11, 页码: 32
作者:  Yu, Haijun;  Tian, Xinyuan;  Weinan, E.;  Li, Qianxiao
收藏  |  浏览/下载：96/0  |  提交时间：2022/04/02
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：113/0  |  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  
Deep learning neural networks for the third-order nonlinear Schrodinger equation: bright solitons, breathers, and rogue waves 期刊论文
COMMUNICATIONS IN THEORETICAL PHYSICS, 2021, 卷号: 73, 期号: 10, 页码: 9
作者:  Zhou, Zijian;  Yan, Zhenya
收藏  |  浏览/下载：101/0  |  提交时间：2022/04/02
third-order nonlinear Schrodinger equation  deep learning  data-driven solitons  data-driven parameter discovery  
Deep learning neural networks for the third-order nonlinear Schr?dinger equation: bright solitons, breathers, and rogue waves 期刊论文
Communications in Theoretical Physics, 2021, 卷号: 73, 期号: 10
作者:  Zhou,Zijian;  Yan,Zhenya
收藏  |  浏览/下载：99/0  |  提交时间：2022/04/02
third-order nonlinear Schr?dinger equation  deep learning  data-driven solitons  data-driven parameter discovery  
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：146/0  |  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：139/0  |  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：134/0  |  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)  
Almost sure convergence of randomised-difference descent algorithm for stochastic convex optimisation 期刊论文
IET CONTROL THEORY AND APPLICATIONS, 2021, 页码: 12
作者:  Geng, Xiaoxue;  Huang, Gao;  Zhao, Wenxiao
收藏  |  浏览/下载：116/0  |  提交时间：2021/10/26
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