Stochastic Configuration Networks: Fundamentals and Algorithms

10 February 2017

Papers citing "Stochastic Configuration Networks: Fundamentals and Algorithms"

23 / 23 papers shown

Title
Recurrent Stochastic Configuration Networks for Temporal Data Analytics Dianhui Wang Gang Dang 29 4 0 21 Jun 2024
Cloud Ensemble Learning for Fault Diagnosis of Rolling Bearings with Stochastic Configuration Networks Wei Dai Jiang Liu Lanhao Wang 19 13 0 02 Jul 2023
Reliable Prediction Intervals with Directly Optimized Inductive Conformal Regression for Deep Learning Haocheng Lei A. Bellotti 26 6 0 02 Feb 2023
Bort: Towards Explainable Neural Networks with Bounded Orthogonal Constraint Borui Zhang Wenzhao Zheng Jie Zhou Jiwen Lu AAML 25 7 0 18 Dec 2022
A New Learning Paradigm for Stochastic Configuration Network: SCN+ Yanshuang Ao Xinyu Zhou Wei Dai 15 1 0 11 Mar 2022
Weighting and Pruning based Ensemble Deep Random Vector Functional Link Network for Tabular Data Classification Qi-Shi Shi Ponnuthurai Nagaratnam Suganthan Rakesh Katuwal 6 22 0 15 Jan 2022
Feature extraction and classification algorithm, which one is more essential? An experimental study on a specific task of vibration signal diagnosis Qiang Liu Jiade Zhang Jingna Liu Zhi-qun Yang 14 13 0 17 Dec 2021
Theory of Deep Convolutional Neural Networks III: Approximating Radial Functions Tong Mao Zhongjie Shi Ding-Xuan Zhou 16 33 0 02 Jul 2021
Demystification of Few-shot and One-shot Learning I. Tyukin A. Gorban Muhammad H. Alkhudaydi Qinghua Zhou 16 13 0 25 Apr 2021
A Modified Batch Intrinsic Plasticity Method for Pre-training the Random Coefficients of Extreme Learning Machines S. Dong Zongwei Li 17 29 0 14 Mar 2021
Cluster-based Input Weight Initialization for Echo State Networks Peter Steiner A. Jalalvand P. Birkholz 20 13 0 08 Mar 2021
Deep Randomized Neural Networks Claudio Gallicchio Simone Scardapane OOD 45 61 0 27 Feb 2020
Error-feedback stochastic modeling strategy for time series forecasting with convolutional neural networks Xinze Zhang Kun He Yukun Bao AI4TS 17 9 0 03 Feb 2020
Theory of neuromorphic computing by waves: machine learning by rogue waves, dispersive shocks, and solitons G. Marcucci D. Pierangeli Claudio Conti 24 109 0 15 Dec 2019
Blessing of dimensionality at the edge I. Tyukin Alexander N. Gorban A. McEwan Sepehr Meshkinfamfard Lixin Tang 13 8 0 30 Sep 2019
Density Encoding Enables Resource-Efficient Randomly Connected Neural Networks Denis Kleyko Mansour Kheffache E. P. Frady U. Wiklund Evgeny Osipov 19 45 0 19 Sep 2019
Fast Construction of Correcting Ensembles for Legacy Artificial Intelligence Systems: Algorithms and a Case Study I. Tyukin Alexander N. Gorban Stephen Green Danil Prokhorov 19 15 0 12 Oct 2018
Autonomous Deep Learning: Incremental Learning of Denoising Autoencoder for Evolving Data Streams Mahardhika Pratama Andri Ashfahani Yew-Soon Ong Savitha Ramasamy E. Lughofer 6 15 0 24 Sep 2018
Randomized Mixture Models for Probability Density Approximation and Estimation Hien Nguyen Dianhui Wang Geoffrey J. McLachlan 9 9 0 23 Apr 2018
Blessing of dimensionality: mathematical foundations of the statistical physics of data A. N. Gorban I. Tyukin 24 145 0 10 Jan 2018
A Method of Generating Random Weights and Biases in Feedforward Neural Networks with Random Hidden Nodes Grzegorz Dudek 13 45 0 13 Oct 2017
Stochastic Configuration Networks Ensemble for Large-Scale Data Analytics Dianhui Wang Caihao Cui BDL 22 112 0 02 Jul 2017
Parsimonious Random Vector Functional Link Network for Data Streams Mahardhika Pratama Plamen Angelov E. Lughofer 6 46 0 10 Apr 2017