"statistical learning theory" Papers

Bridging the Gap Between f-divergences and Bayes Hilbert Spaces

Linus Lach, Alexander Fottner, Yarema Okhrin

Data-Driven Performance Guarantees for Classical and Learned Optimizers

Rajiv Sambharya, Bartolomeo Stellato

Learning with Statistical Equality Constraints

Aneesh Barthakur, Luiz Chamon

Algorithmic Stability Unleashed: Generalization Bounds with Unbounded Losses

Shaojie Li, Bowei Zhu, Yong Liu

A Statistical Theory of Regularization-Based Continual Learning

Xuyang Zhao, Huiyuan Wang, Weiran Huang et al.

Concentration Inequalities for General Functions of Heavy-Tailed Random Variables

Shaojie Li, Yong Liu

FedNS: A Fast Sketching Newton-Type Algorithm for Federated Learning

On Statistical Learning Theory for Distributional Inputs

Christian Fiedler, Pierre-François Massiani, Friedrich Solowjow et al.

On the Consistency of Kernel Methods with Dependent Observations

Pierre-François Massiani, Sebastian Trimpe, Friedrich Solowjow

Smoothness Adaptive Hypothesis Transfer Learning

Haotian Lin, Matthew Reimherr

Stability and Generalization of Stochastic Compositional Gradient Descent Algorithms

Ming Yang, Xiyuan Wei, Tianbao Yang et al.