کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
6865594 679059 2015 10 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Asynchronous gossip principal components analysis
ترجمه فارسی عنوان
تجزیه و تحلیل اجزای اصلی شایعات بی نظیر
کلمات کلیدی
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر هوش مصنوعی
چکیده انگلیسی
This paper deals with Principal Components Analysis (PCA) of data spread over a network where central coordination and synchronous communication between networking nodes are forbidden. We propose an asynchronous and decentralized PCA algorithm dedicated to large scale problems, where “large” simultaneously applies to dimensionality, number of observations and network size. It is based on the integration of a dimension reduction step into a gossip consensus protocol. Unlike other approaches, a straightforward dual formulation makes it suitable when observed dimensions are distributed. We theoretically show its equivalence with a centralized PCA under a low-rank assumption on training data. An experimental analysis reveals that it achieves a good accuracy with a reasonable communication cost even when the low-rank assumption is relaxed.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Neurocomputing - Volume 169, 2 December 2015, Pages 262-271
نویسندگان
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