On Causal and Anticausal Learning

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Authors Dominik Janzing, Kun Zhang, Eleni Sgouritsa, Joris Mooij, Jonas Peters, Bernhard Schoelkopf
Journal/Conference Name Proceedings of the 29th International Conference on Machine Learning, ICML 2012
Paper Category
Paper Abstract We consider the problem of function estimation in the case where an underlying causal model can be inferred. This has implications for popular scenarios such as covariate shift, concept drift, transfer learning and semi-supervised learning. We argue that causal knowledge may facilitate some approaches for a given problem, and rule out others. In particular, we formulate a hypothesis for when semi-supervised learning can help, and corroborate it with empirical results.
Date of publication 2012
Code Programming Language CSS

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