Robustifying Independent Component Analysis by Adjusting for Group-Wise Stationary Noise

التفاصيل البيبلوغرافية
العنوان: Robustifying Independent Component Analysis by Adjusting for Group-Wise Stationary Noise
المؤلفون: Pfister, Niklas, Weichwald, Sebastian, Bühlmann, Peter, Schölkopf, Bernhard
المصدر: Journal of Machine Learning Research, 20(147):1-50, 2019. ( http://www.jmlr.org/papers/v20/18-399.html )
سنة النشر: 2018
المجموعة: Computer Science
Quantitative Biology
Statistics
مصطلحات موضوعية: Statistics - Machine Learning, Computer Science - Machine Learning, Quantitative Biology - Quantitative Methods, Statistics - Applications, Statistics - Methodology
الوصف: We introduce coroICA, confounding-robust independent component analysis, a novel ICA algorithm which decomposes linearly mixed multivariate observations into independent components that are corrupted (and rendered dependent) by hidden group-wise stationary confounding. It extends the ordinary ICA model in a theoretically sound and explicit way to incorporate group-wise (or environment-wise) confounding. We show that our proposed general noise model allows to perform ICA in settings where other noisy ICA procedures fail. Additionally, it can be used for applications with grouped data by adjusting for different stationary noise within each group. Our proposed noise model has a natural relation to causality and we explain how it can be applied in the context of causal inference. In addition to our theoretical framework, we provide an efficient estimation procedure and prove identifiability of the unmixing matrix under mild assumptions. Finally, we illustrate the performance and robustness of our method on simulated data, provide audible and visual examples, and demonstrate the applicability to real-world scenarios by experiments on publicly available Antarctic ice core data as well as two EEG data sets. We provide a scikit-learn compatible pip-installable Python package coroICA as well as R and Matlab implementations accompanied by a documentation at https://sweichwald.de/coroICA/
Comment: equal contribution between Pfister and Weichwald
نوع الوثيقة: Working Paper
URL الوصول: http://arxiv.org/abs/1806.01094
رقم الانضمام: edsarx.1806.01094
قاعدة البيانات: arXiv