Hybrid Random Fields A Scalable Approach To Structure And Parameter Learning In Probabilistic Graphical Models - Info and Reading Options
By Antonino Freno
"Hybrid Random Fields A Scalable Approach To Structure And Parameter Learning In Probabilistic Graphical Models" was published by Springer in 2011.
“Hybrid Random Fields A Scalable Approach To Structure And Parameter Learning In Probabilistic Graphical Models” Metadata:
- Title: ➤ Hybrid Random Fields A Scalable Approach To Structure And Parameter Learning In Probabilistic Graphical Models
- Author: Antonino Freno
- Publisher: Springer
- Publish Date: 2011
“Hybrid Random Fields A Scalable Approach To Structure And Parameter Learning In Probabilistic Graphical Models” Subjects and Themes:
- Subjects: Engineering - Artificial intelligence - Probabilities - Graphical modeling (Statistics) - Statistics, graphic methods
Edition Identifiers:
- The Open Library ID: OL26094308M - OL17506242W
- Online Computer Library Center (OCLC) ID: 739133249
- Library of Congress Control Number (LCCN): 2011925689
- ISBN-13: 9783642203077
- All ISBNs: 9783642203077
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