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Amaury Habrard
Researcher at Centre national de la recherche scientifique
Publications - 149
Citations - 4476
Amaury Habrard is an academic researcher from Centre national de la recherche scientifique. The author has contributed to research in topics: Computer science & Tree (data structure). The author has an hindex of 27, co-authored 139 publications receiving 3590 citations. Previous affiliations of Amaury Habrard include Aix-Marseille University & Jean Monnet University.
Papers
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Proceedings ArticleDOI
Unsupervised Visual Domain Adaptation Using Subspace Alignment
TL;DR: This paper introduces a new domain adaptation algorithm where the source and target domains are represented by subspaces described by eigenvectors, and seeks a domain adaptation solution by learning a mapping function which aligns the source subspace with the target one.
Posted Content
A Survey on Metric Learning for Feature Vectors and Structured Data
TL;DR: A systematic review of the metric learning literature is proposed, highlighting the pros and cons of each approach and presenting a wide range of methods that have recently emerged as powerful alternatives, including nonlinear metric learning, similarity learning and local metric learning.
Posted Content
Joint Distribution Optimal Transportation for Domain Adaptation
TL;DR: This paper proposes a solution of the unsupervised domain adaptation problem with optimal transport, that allows to recover an estimated target $\mathcal{P}^f_t=(X,f(X))$ by optimizing simultaneously the optimal coupling and $f$.
Book ChapterDOI
A Polynomial Algorithm for the Inference of Context Free Languages
TL;DR: It is established that all context free languages that satisfy two constraints on the context distributions can be identified in the limit by this approach.
Proceedings ArticleDOI
Joint Distribution Optimal Transportation for Domain Adaptation
TL;DR: In this article, a non-linear transformation between the joint feature/label space distributions of the two domains P s and P t can be estimated with optimal transport, which corresponds to the minimization of a bound on the target error.