Position: An Empirically Grounded Identifiability Theory Will Accelerate Self Supervised Learning Research

Patrik Reizinger; Randall Balestriero; David Klindt; Wieland Brendel

2025 ICML ICML 2025

Position: An Empirically Grounded Identifiability Theory Will Accelerate Self Supervised Learning Research

Abstract

No abstract available. No abstract was captured for this paper when its proceedings were scraped - most often an older edition published without one online. How the corpus is built.

Authors

Patrik Reizinger, Randall Balestriero, David Klindt, Wieland Brendel

Topics

Machine Learning > Learning Types > Self-Supervised Learning Machine Learning > Optimization & Theory > Learning Theory Deep Learning > Learning Types > Representation Learning

Keywords

training dynamics finite sample identifiability theory inductive biases convergence properties singular identifiability theory

Download PDF