Learning an efficient constructive sampler for graphs

DOI10.1016/j.artint.2016.01.006zbMath1404.68098DBLPjournals/ai/Costa17OpenAlexW2234112207WikidataQ57931583 ScholiaQ57931583MaRDI QIDQ511780

Fabrizio Costa

Publication date: 22 February 2017

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

Full work available at URL: https://doi.org/10.1016/j.artint.2016.01.006

zbMATH Keywords

graph kernelsgraph constructiongraph samplingMetropolis-Hastings sampling

Mathematics Subject Classification ID

Computational methods in Markov chains (60J22) Sampling theory, sample surveys (62D05) Learning and adaptive systems in artificial intelligence (68T05) Grammars and rewriting systems (68Q42)

Uses Software

• gSpan

Cites Work

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• From Frequency to Meaning: Vector Space Models of Semantics
• Equation of State Calculations by Fast Computing Machines
• Understanding the Hastings Algorithm
• Learning Theory and Kernel Machines
• On Estimation of a Probability Density Function and Mode

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