title: Domain Adaptation with Conditional Transferable Components.
abstract: Domain adaptation arises in supervised learning when the training (source domain) and test (target domain) data have different distributions. LetXandYdenote the features and target, respectively, previous work on domain adaptation mainly considers the covariate shift situation where the distribution of the featuresP(X) changes across domains while the conditional distributionP(Y∣X) stays the same. To reduce domain discrepancy, recent methods try to find invariant components [Formula: see text] that have similar [Formula: see text] on different domains by explicitly minimizing a distribution discrepancy measure. However, it is not clear if [Formula: see text] in different domains is also similar whenP(Y∣X) changes. Furthermore, transferable components do not necessarily have to be invariant. If the change in some components is identifiable, we can make use of such components for prediction in the target domain. In this paper, we focus on the case whereP(X∣Y) andP(Y) both change in a causal system in whichYis the cause forX. Under appropriate assumptions, we aim to extract conditional transferable components whose conditional distribution [Formula: see text] is invariant after proper location-scale (LS) transformations, and identify howP(Y) changes between domains simultaneously. We provide theoretical analysis and empirical evaluation on both synthetic and real-world data to show the effectiveness of our method.
authors.affiliation: Centre for Quantum Computation and Intelligent Systems, FEIT, University of Technology Sydney, NSW, Australia.
authors.forename: Mingming
authors.initials: M
authors.lastname: Gong
authors.affiliation: Department of Philosophy, Carnegie Mellon University, Pittsburgh, USA ; Max Plank Institute for Intelligent Systems, Tübingen 72076, Germany.
authors.forename: Kun
authors.initials: K
authors.lastname: Zhang
authors.affiliation: Centre for Quantum Computation and Intelligent Systems, FEIT, University of Technology Sydney, NSW, Australia.
authors.forename: Tongliang
authors.initials: T
authors.lastname: Liu
authors.affiliation: Centre for Quantum Computation and Intelligent Systems, FEIT, University of Technology Sydney, NSW, Australia.
authors.forename: Dacheng
authors.initials: D
authors.lastname: Tao
authors.affiliation: Department of Philosophy, Carnegie Mellon University, Pittsburgh, USA.
authors.forename: Clark
authors.initials: C
authors.lastname: Glymour
authors.affiliation: Max Plank Institute for Intelligent Systems, Tübingen 72076, Germany.
authors.forename: Bernhard
authors.initials: B
authors.lastname: Schölkopf