Piecewise training for structured prediction

DOI10.1007/s10994-009-5112-zzbMath1470.68182OpenAlexW1986916218MaRDI QIDQ1959525

Charles Sutton, Andrew Kachites McCallum

Publication date: 7 October 2010

Published in: Machine Learning (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s10994-009-5112-z

zbMATH Keywords

graphical modelsconditional random fieldsbelief propagationlocal training

Mathematics Subject Classification ID

Inference from stochastic processes and prediction (62M20) Random fields; image analysis (62M40) Learning and adaptive systems in artificial intelligence (68T05) Probabilistic graphical models (62H22)

Related Items (2)

Exploiting symmetries for scaling loopy belief propagation and relational training ⋮ Conditional random fields for pattern recognition applied to structured data

Uses Software

• Stanford Tagger

Cites Work

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