'On the Approximation of Kernel functions', by Paul Dommel, Alois Pichler.

http://jmlr.org/papers/v26/24-0270.html

#kernels #kernel #regularization

On the Approximation of Kernel functions

'Deep Out-of-Distribution Uncertainty Quantification via Weight Entropy Maximization', by Antoine de Mathelin, François Deheeger, Mathilde Mougeot, Nicolas Vayatis.

http://jmlr.org/papers/v26/23-1359.html

#regularization #entropy #gaussian

Deep Out-of-Distribution Uncertainty Quantification via Weight Entropy Maximization

'An Optimal Transport Approach for Computing Adversarial Training Lower Bounds in Multiclass Classification', by Nicolas Garcia Trillos, Matt Jacobs, Jakwang Kim, Matthew Werenski.

http://jmlr.org/papers/v25/24-0268.html

#adversarial #regularization #classifiers

An Optimal Transport Approach for Computing Adversarial Training Lower Bounds in Multiclass Classification

'An Inexact Projected Regularized Newton Method for Fused Zero-norms Regularization Problems', by Yuqia Wu, Shaohua Pan, Xiaoqi Yang.

http://jmlr.org/papers/v25/23-1700.html

#regularization #regularized #gradient

An Inexact Projected Regularized Newton Method for Fused Zero-norms Regularization Problems

'Entropic Gromov-Wasserstein Distances: Stability and Algorithms', by Gabriel Rioux, Ziv Goldfeld, Kengo Kato.

http://jmlr.org/papers/v25/24-0039.html

#regularization #wasserstein #variational

Entropic Gromov-Wasserstein Distances: Stability and Algorithms

'Spectral Regularized Kernel Goodness-of-Fit Tests', by Omar Hagrass, Bharath K. Sriperumbudur, Bing Li.

http://jmlr.org/papers/v25/23-1031.html

#regularization #regularized #spectral

Spectral Regularized Kernel Goodness-of-Fit Tests

'Stochastic Regularized Majorization-Minimization with weakly convex and multi-convex surrogates', by Hanbaek Lyu.

http://jmlr.org/papers/v25/23-0349.html

#regularization #regularized #minimization

Stochastic Regularized Majorization-Minimization with weakly convex and multi-convex surrogates

'Random Smoothing Regularization in Kernel Gradient Descent Learning', by Liang Ding, Tianyang Hu, Jiahang Jiang, Donghao Li, Wenjia Wang, Yuan Yao.

http://jmlr.org/papers/v25/23-0580.html

#regularization #smoothing #gradient

Random Smoothing Regularization in Kernel Gradient Descent Learning

'Functional optimal transport: regularized map estimation and domain adaptation for functional data', by Jiacheng Zhu, Aritra Guha, Dat Do, Mengdi Xu, XuanLong Nguyen, Ding Zhao.

http://jmlr.org/papers/v25/22-0217.html

#transport #regularization #measures

Functional optimal transport: regularized map estimation and domain adaptation for functional data

'On Regularized Radon-Nikodym Differentiation', by Duc Hoan Nguyen, Werner Zellinger, Sergei Pereverzyev.

http://jmlr.org/papers/v25/23-0567.html

#regularization #regularized #estimation

On Regularized Radon-Nikodym Differentiation