Attribute-Distributed Learning: Models, Limits, and Algorithms

DOI10.1109/TSP.2010.2088393zbMath1392.94572OpenAlexW2004477678MaRDI QIDQ4572769

Sanjeev R. Kulkarni, H. Vincent Poor, Haipeng Zheng

Publication date: 18 July 2018

Published in: IEEE Transactions on Signal Processing (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1109/tsp.2010.2088393

Mathematics Subject Classification ID

Nonparametric regression and quantile regression (62G08) Classification and discrimination; cluster analysis (statistical aspects) (62H30) Learning and adaptive systems in artificial intelligence (68T05) Signal theory (characterization, reconstruction, filtering, etc.) (94A12)

Related Items (5)

A sequential predictor retraining algorithm and its application to market prediction ⋮ Combining machine learning and domain decomposition methods for the solution of partial differential equations—A review ⋮ Context-based unsupervised ensemble learning and feature ranking ⋮ A comprehensive review on blockchains for Internet of Vehicles: challenges and directions ⋮ Distributed online semi-supervised support vector machine

This page was built for publication: Attribute-Distributed Learning: Models, Limits, and Algorithms