On the analysis of adaptability in multi-source domain adaptation

DOI10.1007/s10994-019-05823-0zbMath1494.68229OpenAlexW2954193398MaRDI QIDQ2320593

Amaury Habrard, Ievgen Redko, Marc Sebban

Publication date: 23 August 2019

Published in: Machine Learning (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s10994-019-05823-0

zbMATH Keywords

learning theorytransfer learningdomain adaptation

Mathematics Subject Classification ID

Classification and discrimination; cluster analysis (statistical aspects) (62H30) Learning and adaptive systems in artificial intelligence (68T05)

Related Items (1)

A GPM-based algorithm for solving regularized Wasserstein barycenter problems in some spaces of probability measures

Uses Software

• EMD
• Wasserstein GAN

Cites Work

• Domain adaptation and sample bias correction theory and algorithm for regression
• On the rate of convergence in Wasserstein distance of the empirical measure
• Uniqueness and approximate computation of optimal incomplete transportation plans
• Functional density synchronization
• Upper and lower risk bounds for estimating the Wasserstein barycenter of random measures on the real line
• Regularized barycenters in the Wasserstein space
• Unbalanced optimal transport: dynamic and Kantorovich formulations
• The earth mover's distance as a metric for image retrieval
• A theory of learning from different domains
• Distribution's template estimate with Wasserstein metrics
• Existence and consistency of Wasserstein barycenters
• Concerning nonnegative matrices and doubly stochastic matrices
• Barycenters in the Wasserstein Space
• Probability Metrics
• A Hilbert Space Embedding for Distributions
• Data-driven regularization of Wasserstein barycenters with an application to multivariate density registration
• Unnamed Item

This page was built for publication: On the analysis of adaptability in multi-source domain adaptation