Efficient global maximum likelihood estimation through kernel methods

DOI10.1016/j.neunet.2010.03.003zbMath1396.68088OpenAlexW2029911857WikidataQ45150069 ScholiaQ45150069MaRDI QIDQ1784705

Marco Muselli, Danilo Macciò, Cristiano Cervellera

Publication date: 27 September 2018

Published in: Neural Networks (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.neunet.2010.03.003

zbMATH Keywords

maximum likelihood estimationlow-discrepancy sequencesdeterministic learningkernel models

Mathematics Subject Classification ID

Learning and adaptive systems in artificial intelligence (68T05)

Cites Work

• Unnamed Item
• Unnamed Item
• Unnamed Item
• Density estimation via exponential model selection
• Efficient Greedy Learning of Gaussian Mixture Models
• Gaussian sum particle filtering
• Projection pursuit mixture density estimation
• The elements of statistical learning. Data mining, inference, and prediction

This page was built for publication: Efficient global maximum likelihood estimation through kernel methods