Autoplay Next video from Max length

NIPS 2011 Domain Adaptation Workshop: Domain Adaptation with Multiple Latent Domains

889 views · Published 3 February 2012 · 16:38 · Indexed 23 September 2026

Channel: Google TechTalks · 2012 · Science & Technology

Domain Adaptation Workshop: Theory and Application at NIPS 2011
Invited Talk: Domain Adaptation with Multiple Latent Domains by Kate Saenko

Abstract:
Domain adaptation is important for practical applications of supervised learning, as the distribution of inputs can differ significantly between available sources of training data and the test data in a particular target domain. Many domain adaptation methods have been proposed, yet very few of them deal with the case of more than one training domain; methods that do incorporate multiple domains assume that the separation into domains is known a priori, which is not always the case in practice. In this paper, we introduce a method for multi-domain adaptation with unknown domain labels, based on learning nonlinear crossdomain transforms, and apply it to image classification. Our key contribution is a novel version of constrained clustering; unlike many existing constrained clustering algorithms, ours can be shown to provably converge locally while satisfying all constraints. We present experiments on a commonly available image dataset.

NIPS 2011 Domain Adaptation Workshop: Domain Adaptation with Multiple Latent Domains

More from this channel