Work

When is an old example forgotten? Predicting first-misclassification times from the tangent kernel at the task switch

Year: 2026

Type: preprint

Abstract: Preprint, under consideration at Pattern Recognition Letters. We evaluate the empirical neural tangent kernel frozen at the task switch as a predictor of which old examples a two-layer ReLU network first misclassifies under the cross-entropy loss, and when, with random labels and a domain-incremental split of a handwritten-digit dataset. The archive contains the manuscript, the Supplementary material, all code, per-seed results, the protocol fixed before the fresh seeds were run (with a dated explanatory note), and scripts that reproduce every number and figure (see README.txt).

Source: Zenodo (CERN European Organization for Nuclear Research)

DOI: 10.5281/zenodo.23732218

Author: Tanaka, Yusuke

Language: English

Topic: Domain Adaptation and Few-Shot Learning

Subfield: Artificial Intelligence

Field: Computer Science

Domain: Physical Sciences

Open Access status: green

OpenAlex ID: W7224097095

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