日時：１０月１９日（水）　１５：３０～１６：３０ + ε (時間が変更になりました)
場所：DSラーニングコモンズ（データサイエンス棟１F）
アクセス: https://www.ds.shiga-u.ac.jp/access/

講演者：Aapo Hyvärinen 氏 （Gatsby Computational Neuroscience Unit, University College London / Department of Computer Science, University of Helsinki)

題目：「Unsupervised Feature Extraction by Time-Contrastive Learning and Nonlinear ICA」

概要：Nonlinear independent component analysis (ICA) provides an appealing framework for unsupervised feature learning, but the models proposed so far are not identifiable. Here, we first propose a new intuitive principle of unsupervised deep learning from time series which uses the nonstationary structure of the data. Our learning principle, time-contrastive learning (TCL), finds a representation which allows optimal discrimination of time segments (windows). Surprisingly, we show how TCL can be related to a nonlinear ICA model, when ICA is redefined to include temporal nonstationarities. In particular, we show that TCL combined with linear ICA estimates the nonlinear ICA model up to point-wise transformations of the sources, and this solution is unique — thus providing the first identifiability result for nonlinear ICA which is rigorous, constructive, as well as very general. https://arxiv.org/pdf/1605.06336v1.pdf
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