Multiple instance classification: review, taxonomy and comparative study

DOI10.1016/J.ARTINT.2013.06.003zbMath1334.68176OpenAlexW2010792435WikidataQ29026937 ScholiaQ29026937MaRDI QIDQ490423

Jaume Amores

Publication date: 27 August 2015

Published in: Artificial Intelligence (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.artint.2013.06.003

zbMATH Keywords

codebookmulti-instance learningbag-of-words

Mathematics Subject Classification ID

Classification and discrimination; cluster analysis (statistical aspects) (62H30) Learning and adaptive systems in artificial intelligence (68T05) Pattern recognition, speech recognition (68T10)

Related Items (15)

Classification in the multiple instance learning framework via spherical separation ⋮ Multiple instance classification via quadratic programming ⋮ Maximum margin partial label learning ⋮ Literature reviews in operations research: a new taxonomy and a meta review ⋮ The semiproximal SVM approach for multiple instance learning: a kernel-based computational study ⋮ Multi-instance learning by maximizing the area under receiver operating characteristic curve ⋮ Semisupervised, Multilabel, Multi-Instance Learning for Structured Data ⋮ Bag similarity network for deep multi-instance learning ⋮ Instance-level accuracy versus bag-level accuracy in multi-instance learning ⋮ Multi-Instance Dimensionality Reduction via Sparsity and Orthogonality ⋮ Weakly supervised classification in high energy physics ⋮ Supervised aggregated feature learning for multiple instance classification ⋮ Diversified dictionaries for multi-instance learning ⋮ Generalized dictionaries for multiple instance learning ⋮ A maximum-margin multisphere approach for binary multiple instance learning

Uses Software

• UCI-ml
• LIBSVM
• EMD

Cites Work

• Unnamed Item
• Multiple instance classification via successive linear programming
• Solving the multiple instance problem with axis-parallel rectangles.
• The earth mover's distance as a metric for image retrieval
• Machine Learning: ECML 2004

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