دورية أكاديمية

On the convergence of maximum variance unfolding

التفاصيل البيبلوغرافية
العنوان: On the convergence of maximum variance unfolding
المؤلفون: Arias-Castro, Ery, Pelletier, Bruno
المساهمون: Department of Mathematics Univ California San Diego (MATH - UC San Diego), University of California San Diego (UC San Diego), University of California (UC)-University of California (UC), Institut de Recherche Mathématique de Rennes (IRMAR), Université de Rennes (UR)-Institut National des Sciences Appliquées - Rennes (INSA Rennes), Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-École normale supérieure - Rennes (ENS Rennes)-Université de Rennes 2 (UR2)-Centre National de la Recherche Scientifique (CNRS)-INSTITUT AGRO Agrocampus Ouest, Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)
المصدر: ISSN: 1532-4435.
بيانات النشر: HAL CCSD
Microtome Publishing
سنة النشر: 2013
المجموعة: Archive Ouverte de l'Université Rennes (HAL)
مصطلحات موضوعية: Maximum Variance Unfolding, Isometric embedding, U-processes, empirical processes, proximity graphs, 62G05, 62G20, [STAT.ML]Statistics [stat]/Machine Learning [stat.ML]
الوصف: International audience ; Maximum Variance Unfolding is one of the main methods for (nonlinear) dimensionality reduction. We study its large sample limit, providing specific rates of convergence under standard assumptions. We find that it is consistent when the underlying submanifold is isometric to a convex subset, and we provide some simple examples where it fails to be consistent.
نوع الوثيقة: article in journal/newspaper
اللغة: English
العلاقة: info:eu-repo/semantics/altIdentifier/arxiv/1209.0016; hal-00771311; https://hal.science/hal-00771311Test; ARXIV: 1209.0016
الإتاحة: https://hal.science/hal-00771311Test
رقم الانضمام: edsbas.EDC0960
قاعدة البيانات: BASE