Online Stochastic DCA With Applications to Principal Component Analysis

Stochastic algorithms are well-known for their performance in the era of big data. In this article, we study nonsmooth stochastic Difference-of-Convex functions (DC) programs-the major class of nonconvex stochastic optimization, which have a variety of applications in divers domains, in particular,...

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Veröffentlicht in:	IEEE transaction on neural networks and learning systems 2024-05, Vol.35 (5), p.7035-7047
Hauptverfasser:	Le Thi, Hoai An, Luu, Hoang Phuc Hau, Dinh, Tao Pham
Format:	Artikel
Sprache:	eng
Schlagworte:	Algorithms Big Data Computer Science Convex functions DC~algorithm (DCA) Difference of Convex functions (DC) programming Divers Learning algorithms Machine learning Machine learning algorithms Martingales Mathematics nonconvex optimization online stochastic DCA (osDCA) Optimization Principal component analysis principal component analysis (PCA) Principal components analysis Programming Stochastic processes Stochasticity
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