"statistical learning theory" Papers
12 papers found
Conference
Bridging the Gap Between f-divergences and Bayes Hilbert Spaces
Linus Lach, Alexander Fottner, Yarema Okhrin
ICLR 2025
Data-Driven Performance Guarantees for Classical and Learned Optimizers
Rajiv Sambharya, Bartolomeo Stellato
NEURIPS 2025arXiv:2404.13831
10
citations
Learning with Statistical Equality Constraints
Aneesh Barthakur, Luiz Chamon
NEURIPS 2025arXiv:2511.14320
PAC-Bayes Bounds for Multivariate Linear Regression and Linear Autoencoders
Ruixin Guo, Ruoming Jin, Xinyu Li et al.
NEURIPS 2025arXiv:2512.12905
1
citations
Algorithmic Stability Unleashed: Generalization Bounds with Unbounded Losses
Shaojie Li, Bowei Zhu, Yong Liu
ICML 2024
A Statistical Theory of Regularization-Based Continual Learning
Xuyang Zhao, Huiyuan Wang, Weiran Huang et al.
ICML 2024arXiv:2406.06213
31
citations
Concentration Inequalities for General Functions of Heavy-Tailed Random Variables
Shaojie Li, Yong Liu
ICML 2024spotlight
FedNS: A Fast Sketching Newton-Type Algorithm for Federated Learning
Jian Li, Yong Liu, Wei Wang et al.
AAAI 2024paperarXiv:2401.02734
7
citations
On Statistical Learning Theory for Distributional Inputs
Christian Fiedler, Pierre-François Massiani, Friedrich Solowjow et al.
ICML 2024
On the Consistency of Kernel Methods with Dependent Observations
Pierre-François Massiani, Sebastian Trimpe, Friedrich Solowjow
ICML 2024arXiv:2406.06101
2
citations
Smoothness Adaptive Hypothesis Transfer Learning
Haotian Lin, Matthew Reimherr
ICML 2024arXiv:2402.14966
11
citations
Stability and Generalization of Stochastic Compositional Gradient Descent Algorithms
Ming Yang, Xiyuan Wei, Tianbao Yang et al.
ICML 2024arXiv:2307.03357
3
citations