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Linear screening for high-dimensional computer experiments 期刊论文
STAT, 2021, 卷号: 10, 期号: 1, 页码: 9
作者:  Li, Chunya;  Chen, Daijun;  Xiong, Shifeng
收藏  |  浏览/下载：99/0  |  提交时间：2022/04/02
best linear approximation  best subset regression  nonlinear model  sure independence screening  
Stein variational gradient descent with local approximations 期刊论文
COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING, 2021, 卷号: 386, 页码: 20
作者:  Yan, Liang;  Zhou, Tao
收藏  |  浏览/下载：104/0  |  提交时间：2022/04/02
Stein variational gradient decent  Bayesian inference  Deep learning  Local approximation  
Towards embedding information diffusion data for understanding big dynamic networks 期刊论文
NEUROCOMPUTING, 2021, 卷号: 466, 页码: 265-284
作者:  Yang, Hong;  Zhang, Peng;  Wang, Haishuai;  Zhou, Chuan;  Li, Zhao;  Gao, Li;  Tan, Qingfeng
收藏  |  浏览/下载：133/0  |  提交时间：2022/04/02
Network coarsening  Information diffusion  Graph data mining  
A parallel orbital-updating based optimization method for electronic structure calculations 期刊论文
JOURNAL OF COMPUTATIONAL PHYSICS, 2021, 卷号: 445, 页码: 17
作者:  Dai, Xiaoying;  Liu, Zhuang;  Zhang, Xin;  Zhou, Aihui
收藏  |  浏览/下载：105/0  |  提交时间：2022/04/02
Density functional theory  Electronic structure calculations  Kohn-Sham energy functional minimization problem  Parallel orbital-updating  Optimization method  
Learning with smooth Hinge losses 期刊论文
NEUROCOMPUTING, 2021, 卷号: 463, 页码: 379-387
作者:  Luo, JunRu;  Qiao, Hong;  Zhang, Bo
收藏  |  浏览/下载：121/0  |  提交时间：2022/04/02
Smooth Hinge loss  Convex surrogate loss  Support vector machine  Trust region Newton method  
Learning graph attention-aware knowledge graph embedding 期刊论文
NEUROCOMPUTING, 2021, 卷号: 461, 页码: 516-529
作者:  Li, Chen;  Peng, Xutan;  Niu, Yuhang;  Zhang, Shanghang;  Peng, Hao;  Zhou, Chuan;  Li, Jianxin
收藏  |  浏览/下载：136/0  |  提交时间：2022/04/02
Knowledge graph embedding  Graph attention mechanism  Entity typing  Link prediction  
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：119/0  |  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：159/0  |  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：143/0  |  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：153/0  |  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)