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08/13/2023
Weighted Sparse Partial Least Squares for Joint Sample and Feature Selection
Sparse Partial Least Squares (sPLS) is a common dimensionality reduction...
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12/01/2022
Rethinking Two Consensuses of the Transferability in Deep Learning
Deep transfer learning (DTL) has formed a long-term quest toward enablin...
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10/31/2022
Learning to Optimize Permutation Flow Shop Scheduling via Graph-based Imitation Learning
The permutation flow shop scheduling (PFSS), aiming at finding the optim...
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06/03/2022
MetaLR: Layer-wise Learning Rate based on Meta-Learning for Adaptively Fine-tuning Medical Pre-trained Models
When applying transfer learning for medical image analysis, downstream t...
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11/22/2020
Towards Class-Specific Unit
Class selectivity is an attribute of a unit in deep neural networks, whi...
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04/13/2018
Regularized Singular Value Decomposition and Application to Recommender System
Singular value decomposition (SVD) is the mathematical basis of principa...
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04/06/2018
Minimal Support Vector Machine
Support Vector Machine (SVM) is an efficient classification approach, wh...
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06/20/2017
Outlier Regularization for Vector Data and L21 Norm Robustness
In many real-world applications, data usually contain outliers. One popu...
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05/28/2017
L1-norm Error Function Robustness and Outlier Regularization
In many real-world applications, data come with corruptions, large error...
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05/23/2017
Multiple Images Recovery Using a Single Affine Transformation
In many real-world applications, image data often come with noises, corr...
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10/14/2016
A Harmonic Mean Linear Discriminant Analysis for Robust Image Classification
Linear Discriminant Analysis (LDA) is a widely-used supervised dimension...
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10/14/2016
Kernel Alignment Inspired Linear Discriminant Analysis
Kernel alignment measures the degree of similarity between two kernels. ...
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05/04/2016
Accelerating Deep Learning with Shrinkage and Recall
Deep Learning is a very powerful machine learning model. Deep Learning t...
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02/26/2009
