Mixed-integer quadratic optimization and iterative clustering techniques for semi-supervised support vector machines

DOI10.1007/s11750-024-00668-wMaRDI QIDQ6635845

Jan Pablo Burgard, Martin Schmidt, Maria Eduarda Pinheiro

Publication date: 12 November 2024

Published in: Top (Search for Journal in Brave)

zbMATH Keywords

clusteringsupport vector machinessemi-supervised learningmixed-integer quadratic optimization

Mathematics Subject Classification ID

Applications of mathematical programming (90C90) Mixed integer programming (90C11) Artificial intelligence (68T99) Computational methods for problems pertaining to operations research and mathematical programming (90-08)

Cites Work

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• The planar \(k\)-means problem is NP-hard
• Estimation of regional transition probabilities for spatial dynamic microsimulations from survey data lacking in regional detail
• NP-hardness of Euclidean sum-of-squares clustering
• Support-vector networks
• Inverse probability weighting for clustered nonresponse
• Least squares quantization in PCM
• JuMP: A Modeling Language for Mathematical Optimization

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