In our new model, we enforce the intra-class reconstruction residual of each sample to be smaller than the inter-class reconstruction residual by a large margin ...

In our new model, we enforce the intra-class reconstruction residual of each sample to be smaller than the inter-class reconstruction residual by a large margin ...

To overcome this limitation, we propose a new robust metric learning approach by introducing the maximum correntropy crite- rion to deal with real-world ...

This work proposes a new robust metric learning approach by introducing the maximum correntropy criterion to deal with real-world malicious occlusions or ...

topic with many real-world applications. Most existing metric learning methods aim to learn an optimal Mahalanobis distance matrix M, under which data ...

TL;DR: This work proposes a new robust metric learning approach by introducing the maximum correntropy criterion to deal with real-world malicious ...

Jun 12, 2018 · Authors: Jie Xu (University of Pittsburgh); Lei Luo (University of Pittsburgh); Cheng Deng (Xidian University); Heng Huang (University of ...

Jie Xu, Lei Luo, Cheng Deng , Heng Huang: New Robust Metric Learning Model Using Maximum Correntropy Criterion. KDD 2018: 2555-2564. manage site settings.

Jul 8, 2024 · In this paper, to improve the robustness performance, we develop a mixture correntropy criterion where two Laplacian kernel functions are combined as the ...

In our new model, we enforce the intra-class reconstruction residual of each sample to be smaller than the inter-class reconstruction residual by a large margin ...