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Open Problem: Learning with Variational Objectives on Measures

Year: 2023

Type: preprint

Abstract: The theory of statistical learning has focused on variational objectives expressed on functions. In this note, we discuss motivations to write similar objectives on measures, in particular to discuss out-of-distribution generalization and weakly-supervised learning. It raises a natural question: can one cast usual statistical learning results to objectives expressed on measures? Does the resulting construction lead to new algorithms of practical interest?

Source: arXiv (Cornell University)

DOI: 10.48550/arxiv.2306.11928

Authors: Cabannes, Vivien, Domingo-Enrich, Carles

Language: English

Topic: Machine Learning and Algorithms

Subfield: Artificial Intelligence

Field: Computer Science

Domain: Physical Sciences

Open Access status: green

OpenAlex ID: W4381713219

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