Now Publishers Patterns of Scalable Bayesian Inference (Foundations and Trends (R) in Machine Learning)

Name: Patterns of Scalable Bayesian Inference (Foundations and Trends (R) in Machine Learning)
Brand: Now Publishers
Price: 78.95 GBP
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AI & Machine Learning

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Description

Datasets are growing not just in size but in complexity, creating a demand for rich models and quantification of uncertainty. Bayesian methods are an excellent fit for this demand, but scaling Bayesian inference is a challenge. In response to this challenge, there has been considerable recent work based on varying assumptions about model structure, underlying computational resources, and the importance of asymptotic correctness. As a result, there is a zoo of ideas with a wide range of assumptions and applicability. Patterns of Scalable Bayesian Inference seeks to identify unifying principles, patterns, and intuitions for scaling Bayesian inference. It examines how these techniques can be scaled up to larger problems and scaled out across parallel computational resources. It reviews existing work on utilizing modern computing resources with both MCMC and variational approximation techniques. From this taxonomy of ideas, it characterizes the general principles that have proven successful for designing scalable inference procedures and addresses some of the significant open questions and challenges.

Product Specifications

Brand: Now Publishers
Format: paperback
ASIN: 1680832182
Category: Books > Subjects > Computing & Internet > Computer Science > AI & Machine Learning
Domain: Amazon UK
Release Date: 17 November 2016
Listed Since: 21 November 2016

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Now Publishers Patterns of Scalable Bayesian Inference (Foundations and Trends (R) in Machine Learning)

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