2 papers
cs.LG2024
A separability-based approach to quantifying generalization: which layer is best?
Luciano Dyballa, Evan Gerritz, Steven W. Zucker
Generalization to unseen data remains poorly understood for deep learning classification and foundation models, especially in the open set scenario. How can one assess the ability…
cs.CV2024
Zero-shot generalization across architectures for visual classification
Evan Gerritz, Luciano Dyballa, Steven W. Zucker
Generalization to unseen data is a key desideratum for deep networks, but its relation to classification accuracy is unclear. Using a minimalist vision dataset and a measure of gen…