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Stochastic Learning for Sparse Discrete Markov Random Fields with Controlled Gradient Approximation Error
We study the L(1)-regularized maximum likelihood estimator/estimation (MLE) problemfor discrete Markov random fields (MRFs), where efficient and scalable learning requires both sparse regularization and approximate inference. To address these challenges, we consider a stochastic learning framework c...
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| Publicado no: | Uncertain Artif Intell |
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| Main Authors: | , , , , |
| Formato: | Artigo |
| Idioma: | Inglês |
| Publicado em: |
2018
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| Assuntos: | |
| Acesso em linha: | https://ncbi.nlm.nih.gov/pmc/articles/PMC6292514/ https://ncbi.nlm.nih.gov/pubmed/30555282 |
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