drwuHUST/Patch-Learning

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7
Rank 2,294,772 (Top 46 %)
Language
MATLAB
Created over 5 years ago
Updated about 4 years ago

drwuHUST/Patch-Learning

drwuHUST

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Matlab source code of the paper "D. Wu and J.M. Mendel, Patch Learning, IEEE Trans. on Fuzzy Systems, 28(9):1996-2008, 2020"

TLBCI

Matlab source code of the paper "D. Wu, X. Jiang, R. Peng, W. Kong, J. Huang and Z. Zeng, Transfer Learning for Motor Imagery Based Brain-Computer Interfaces: A Complete Pipeline, Information Sciences, 2021, submitted."

MTGA

Matlab source code of the paper "D. Wu and X. Tan, Multitasking Genetic Algorithm (MTGA) for Fuzzy System Optimization, IEEE Trans. on Fuzzy Systems, 28(6), pp. 1050-1061, 2020."

MBGD_RDA

Matlab source code of the paper "D. Wu, Y. Yuan, J. Huang and Y. Tan*, Optimize TSK Fuzzy Systems for Regression Problems: Mini-Batch Gradient Descent with Regularization, DropRule and AdaBound (MBGD-RDA), IEEE Trans. on Fuzzy Systems, 28(5), pp. 1003-1015, 2020."

MBGD_UR_BN

Matlab source code of the paper "Y. Cui, D. Wu* and J. Huang*, "Optimize TSK Fuzzy Systems for Classification Problems: Mini-Batch Gradient Descent with Uniform Regularization and Batch Normalization," IEEE Trans. on Fuzzy Systems, 28(12):3065-3075, 2020." Python source code is available at https://github.com/YuqiCui/TSK_BN_UR

iGS

Matlab source code of the paper: D. Wu*, C-T Lin and J. Huang*, "Active Learning for Regression Using Greedy Sampling," Information Sciences, vol. 474, pp. 90-105, 2019.

iRDM

Matlab source code of the iRDM algorithm in the paper: Z. Liu, X. Jiang, H. Luo, W. Fang, J. Liu and D. Wu*, "Pool-Based Unsupervised Active Learning for Regression Using Iterative Representativeness-Diversity Maximization (iRDM)," Pattern Recognition Letters, 142:11-19, 2021.

IRD

Matlab code of the IRD algorithm in the paper: 刘子昂, 蒋雪, 伍冬睿, "基于池的无监督线性回归主动学习," 自动化学报, 2020. Or the English version here: https://arxiv.org/pdf/2001.05028.pdf

sAL

Matlab source code of the paper: D. Wu, "Pool-based sequential active learning for regression," IEEE Trans. on Neural Networks and Learning Systems, 30(5), pp. 1348-1359, 2019.