Broad Learning System under Label Noise: A Novel Reweighting Framework with Logarithm Kernel and Mixture Autoencoder
J Shen, H Zhao, W Deng - Sensors, 2024 - mdpi.com
The Broad Learning System (BLS) has demonstrated strong performance across a variety of
problems. However, BLS based on the Minimum Mean Square Error (MMSE) criterion is …
problems. However, BLS based on the Minimum Mean Square Error (MMSE) criterion is …
When broad learning system meets label noise learning: A reweighting learning framework
L Liu, J Chen, B Yang, Q Feng… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
Broad learning system (BLS) is a novel neural network with efficient learning and expansion
capacity, but it is sensitive to noise. Accordingly, the existing robust broad models try to …
capacity, but it is sensitive to noise. Accordingly, the existing robust broad models try to …
Pattern classification with corrupted labeling via robust broad learning system
Most of the existing classification systems assume that the data used is high-quality labeled.
However, the labeling process in real-world may inevitably introduce corruptions into labels …
However, the labeling process in real-world may inevitably introduce corruptions into labels …
Regularized discriminative broad learning system for image classification
Because of its simple network structure and efficient learning mode, the Broad Learning
System (BLS) has achieved impressive performance in image classification tasks …
System (BLS) has achieved impressive performance in image classification tasks …
Discriminative group-sparsity constrained broad learning system for visual recognition
Abstract Broad Learning System (BLS) is an emerging network paradigm that has received
considerable attention in the regression and classification fields. However, there are two …
considerable attention in the regression and classification fields. However, there are two …
Discriminative elastic-net broad learning systems for visual classification
The broad learning system (BLS) has garnered significant attention in the realm of visual
classification due to its exceptional balance between accuracy and efficiency. However, the …
classification due to its exceptional balance between accuracy and efficiency. However, the …
Progressive ensemble kernel-based broad learning system for noisy data classification
Z Yu, K Lan, Z Liu, G Han - IEEE Transactions on Cybernetics, 2021 - ieeexplore.ieee.org
The broad learning system (BLS) is an algorithm that facilitates feature representation
learning and data classification. Although weights of BLS are obtained by analytical …
learning and data classification. Although weights of BLS are obtained by analytical …
Broad learning system based on the quantized minimum error entropy criterion
S Zhang, Z Liu, CLP Chen - Science China Information Sciences, 2022 - Springer
The broad learning system (BLS) based on the minimum mean square error (MMSE)
criterion can achieve outstanding performance without spending too much time in various …
criterion can achieve outstanding performance without spending too much time in various …
Broad learning system based on maximum correntropy criterion
As an effective and efficient discriminative learning method, broad learning system (BLS)
has received increasing attention due to its outstanding performance in various regression …
has received increasing attention due to its outstanding performance in various regression …
Broad learning system based on maximum multi-kernel correntropy criterion
H Zhao, X Lu - Neural Networks, 2024 - Elsevier
The broad learning system (BLS) is an effective machine learning model that exhibits
excellent feature extraction ability and fast training speed. However, the traditional BLS is …
excellent feature extraction ability and fast training speed. However, the traditional BLS is …