Large scale multi-label learning using Gaussian processes
type: Item
instance of: scholarly article
title: Large scale multi-label learning using Gaussian processes
author: Aristeidis Panos
author: Petros Dellaportas
author: Michalis K. Titsias
published in: Machine Learning
publication date: 2021-11-24T00:00:00Z
Mathematics Subject Classification ID: 68T05
zbMATH DE Number: 7432827
zbMATH Keywords: multi-label learning
zbMATH Keywords: Gaussian process
zbMATH Keywords: variational inference
zbMATH Keywords: Bayesian nonparametrics
cites work: CRAFTML
cites work: Q5396647
cites work: Kernels for vector-valued functions: a review
cites work: Data scarcity, robustness and extreme multi-label classification
cites work: Q4637023
cites work: Sparse on-line Gaussian processes
cites work: Bayesian multi-instance multi-label learning using Gaussian process prior
cites work: Q2933843
cites work: Bonsai: diverse and shallow trees for extreme multi-label classification
cites work: Q3093326
cites work: ML-KNN: A lazy learning approach to multi-label learning
describes a project that uses: CRAFTML
describes a project that uses: ML-KNN
describes a project that uses: FastXML
describes a project that uses: AnnexML
describes a project that uses: DiSMEC
describes a project that uses: word2vec
describes a project that uses: WSABIE
MaRDI profile type: Publication
full work available at URL: s10994-021-05952-5
OpenAlex ID: W3155957385
DOI: 10.1007/S10994-021-05952-5
description: scientific article; zbMATH DE number 7432827