English | 繁體

Search in the results

UM

Browse/Search Results:  1-10 of 12 Help

Selected(0)Clear Items/Page:    Sort:
An Efficient Algorithm for the Incremental Broad Learning System by Inverse Cholesky Factorization of a Partitioned Matrix Journal article
Zhu, Hufei, Liu, Zhulin, Philip Chen, C. L., Liang, Yanyang. An Efficient Algorithm for the Incremental Broad Learning System by Inverse Cholesky Factorization of a Partitioned Matrix[J]. IEEE Access, 2021, 9, 19294-19303.
Authors:  Zhu, Hufei;  Liu, Zhulin;  Philip Chen, C. L.;  Liang, Yanyang
Favorite | TC[WOS]:4 TC[Scopus]:2  IF:3.4/3.7 | Submit date：2022/05/13
Added Nodes  Broad Learning System (Bls)  Efficient Algorithms  Incremental Learning  Inverse Cholesky Factorization  Partitioned Matrix  Pseudoinverse  Random Vector Functional-link Neural Networks (Rvflnn)  Single Layer Feedforward Neural Networks (Slfn)  
A new learning paradigm for random vector functional-link network: RVFL+ Journal article
Zhang,Peng Bo, Yang,Zhi Xin. A new learning paradigm for random vector functional-link network: RVFL+[J]. Neural Networks, 2020, 122, 94-105.
Authors:  Zhang,Peng Bo;  Yang,Zhi Xin
Favorite | TC[WOS]:69 TC[Scopus]:77  IF:6.0/7.9 | Submit date：2021/03/11
Rvfl++++  Krvfl++++  Learning Using Privileged Information  The Rademacher Complexity  Svm++++  Random Vector Functional Link Networks  
Universal Approximation Capability of Broad Learning System and Its Structural Variations Journal article
Chen,C. L.Philip, Liu,Zhulin, Feng,Shuang. Universal Approximation Capability of Broad Learning System and Its Structural Variations[J]. IEEE Transactions on Neural Networks and Learning Systems, 2019, 30(4), 1191-1204.
Authors:  Chen,C. L.Philip;  Liu,Zhulin;  Feng,Shuang
Favorite | TC[WOS]:367 TC[Scopus]:435  IF:10.2/10.4 | Submit date：2021/03/09
Broad Learning System (Bls)  Deep Learning  Face Recognition  Functional Link Neural Networks (Flnns)  Nonlinear Function Approximation  Time-variant Big Data Modeling  Universal Approximation  
Broad Learning System: An Effective and Efficient Incremental Learning System Without the Need for Deep Architecture Journal article
Chen, C. L. Philip, Liu, Zhulin. Broad Learning System: An Effective and Efficient Incremental Learning System Without the Need for Deep Architecture[J]. IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, 2018, 29(1), 10-24.
Authors:  Chen, C. L. Philip;  Liu, Zhulin
Favorite | TC[WOS]:984 TC[Scopus]:1413  IF:10.2/10.4 | Submit date：2018/10/30
Big Data  Big Data Modeling  Broad Learning System (Bls)  Deep Learning  Incremental Learning  Random Vector Functional-link Neural Networks (Rvflnn)  Single Layer Feedforward Neural Networks (Slfn)  Singular Value Decomposition (Svd)  
Broad learning system: Feature extraction based on K-means clustering algorithm Conference paper
Liu Z., Zhou J., Chen C.L.P.. Broad learning system: Feature extraction based on K-means clustering algorithm[C], 2017, 683-687.
Authors:  Liu Z.;  Zhou J.;  Chen C.L.P.
Favorite | TC[WOS]:31 TC[Scopus]:45 | Submit date：2019/02/11
Broad Learning System  Deep Learning  Feature Representation  Incremental Learning  K-means  Random Vector Functional Link Networks  Single Layer Feedforward Neural Networks  Svd  
Broad learning system: A new learning paradigm and system without going deep Conference paper
Chen C.L.P., Liu Z.. Broad learning system: A new learning paradigm and system without going deep[C], 2017, 1271-1276.
Authors:  Chen C.L.P.;  Liu Z.
Favorite | TC[WOS]:57 TC[Scopus]:76 | Submit date：2019/02/11
Broad Learning System  Deep Learning  Random Vector Functional Link Networks  Single Layer Feedforward Neural Networks  
Broad Learning System: structural extensions on single-layer and multi-layer neural networks Conference paper
Liu, Zhulin, Chen, C. L. Philip, IEEE. Broad Learning System: structural extensions on single-layer and multi-layer neural networks[C], 345 E 47TH ST, NEW YORK, NY 10017 USA:IEEE, 2017, 136-141.
Authors:  Liu, Zhulin;  Chen, C. L. Philip;  IEEE
Favorite | TC[WOS]:36 TC[Scopus]:49 | Submit date：2018/10/30
Single Layer Feedforward Neural Networks  Random Vector Functional Link Networks  Broad Learning System  Incremental Learning  Extremal Learning Machine  Radial Basis Function Networks  Hierarchical Extremal Learning Machine  
Broad Learning System: a new learning paradigm and system without going deep Conference paper
Chen, C. L. Philip, Liu, Zhulin, IEEE. Broad Learning System: a new learning paradigm and system without going deep[C], 345 E 47TH ST, NEW YORK, NY 10017 USA:IEEE, 2017, 1271-1276.
Authors:  Chen, C. L. Philip;  Liu, Zhulin;  IEEE
Favorite | TC[WOS]:57 TC[Scopus]:76 | Submit date：2018/10/30
Single Layer Feedforward Neural Networks  Random Vector Functional Link Networks  Broad Learning System  Deep Learning  
Broad Learning System: Feature extraction based on K-means clustering algorithm Conference paper
Liu, Zhulin, Zhou, Jin, Chen, C. L. Philip, IEEE. Broad Learning System: Feature extraction based on K-means clustering algorithm[C], 345 E 47TH ST, NEW YORK, NY 10017 USA:IEEE, 2017, 683-687.
Authors:  Liu, Zhulin;  Zhou, Jin;  Chen, C. L. Philip;  IEEE
Favorite | TC[WOS]:31 TC[Scopus]:45 | Submit date：2018/10/30
Single Layer Feedforward Neural Networks  Svd  Random Vector Functional Link Networks  Broad Learning System  Incremental Learning  Deep Learning  K-means  Feature Representation  
Camera motion classification using a genetic functional-link neural network Conference paper
Chen C.L.P., Bhumireddy C., Darvemula P.K.. Camera motion classification using a genetic functional-link neural network[C], 2004, 2343-2348.
Authors:  Chen C.L.P.;  Bhumireddy C.;  Darvemula P.K.
Favorite |  | Submit date：2019/02/11
Camera motion classification  Functional-link networks  Genetic algorithms  MPEG