Kernel PCA for Out-of-Distribution Detection: Non-Linear Kernel Selection and Approximation
cs.LG, cs.CV
Submitted: 2025-05-21
Updated: 2026-07-14
Comments: This study is an extension of its conference version published in NeurIPS'24, see https://proceedings.neurips.cc/paper_files/paper/2024/hash/f2543511e5f4d4764857f9ad833a977d-Abstract-Conference.html
Journal ref: IEEE Trans. Pattern Anal. Mach. Intell. 48(10): 13220-13235 (2026)
DOI: 10.1109/TPAMI.2026.3705778
License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Terminology
Related papers
- Polynomial-Augmented Neural Networks (PANNs) with Weak Orthogonality Constraints for Enhanced Function and PDE Approximation
- AIRL-S: Unifying Reinforcement Learning and Search-Based Test-Time Scaling via Adversarial Inverse Reinforcement Learning
- Transformers as Bayesian In-Context Experimenters: Smoothness-Adaptive Efficient ATE Estimation
- Convergence issues in Relational Concept Analysis based on AOC-posets
- Beliefs Beyond Posteriors: The Predictive Cost of ELBO Binding
- Understanding Diffusion Models via Ratio-Based Function Approximation with SignReLU Networks