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Bibliographic Details
Main Author: García, Joaquín Sánchez
Format: Preprint
Published: 2024
Subjects:
Online Access:https://arxiv.org/abs/2403.02432
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author García, Joaquín Sánchez
author_facet García, Joaquín Sánchez
contents We study a new technique for understanding convergence of learning agents under small modifications of data. We show that such convergence can be understood via an analogue of Fatou's lemma which yields gamma-convergence. We show it's relevance and applications in general machine learning tasks and domain adaptation transfer learning.
format Preprint
id arxiv_https___arxiv_org_abs_2403_02432
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle On the impact of measure pre-conditionings on general parametric ML models and transfer learning via domain adaptation
García, Joaquín Sánchez
Machine Learning
Optimization and Control
We study a new technique for understanding convergence of learning agents under small modifications of data. We show that such convergence can be understood via an analogue of Fatou's lemma which yields gamma-convergence. We show it's relevance and applications in general machine learning tasks and domain adaptation transfer learning.
title On the impact of measure pre-conditionings on general parametric ML models and transfer learning via domain adaptation
topic Machine Learning
Optimization and Control
url https://arxiv.org/abs/2403.02432