Sofiane Dhouib

Revisiting $(\epsilon, \gamma, \tau)$-similarity learning for domain adaptation

Similarity learning is an active research area in machine learning that tackles the problem of finding a similarity function tailored to an observable data sample in order to achieve efficient classification. This learning scenario has been generally formalized by the means of a $(\epsilon, \gamma,…