Nonparametric Distributed Learning Architecture for Big Data: Algorithm and Applications

• Published in: IEEE transactions on big data Vol. 5; no. 2; pp. 166 - 179
• Main Authors: Bruce, Scott, Li, Zeda, Yang, Hsiang-Chieh, Mukhopadhyay, Subhadeep
• Format: Journal Article
• Language: English
• Published: Piscataway The Institute of Electrical and Electronics Engineers, Inc. (IEEE) 01.06.2019
• Subjects: Algorithms; Analytical models; Big Data; Computational modeling; Computer architecture; Data analysis; Data management; Data models; data-parallelism; Datasets; Distributed databases; distributed statistical learning; heterogeneity; Inference algorithms; LP transformation; Machine learning; Meta-analysis; Nonparametric mixed data modeling; Nonparametric statistics; Parallel processing; Statistical inference; Statistical models

Dramatic increases in the size and complexity of modern datasets have made traditional “centralized” statistical inference prohibitive. In addition to computational challenges associated with big data learning, the presence of numerous data types (e.g., discrete, continuous, categorical, etc.) makes...