Boosted Statistical Relational Learners

Boosted Statistical Relational Learners
Author :
Publisher : Springer
Total Pages : 79
Release :
ISBN-10 : 9783319136448
ISBN-13 : 3319136445
Rating : 4/5 (445 Downloads)

Book Synopsis Boosted Statistical Relational Learners by : Sriraam Natarajan

Download or read book Boosted Statistical Relational Learners written by Sriraam Natarajan and published by Springer. This book was released on 2015-03-03 with total page 79 pages. Available in PDF, EPUB and Kindle. Book excerpt: This SpringerBrief addresses the challenges of analyzing multi-relational and noisy data by proposing several Statistical Relational Learning (SRL) methods. These methods combine the expressiveness of first-order logic and the ability of probability theory to handle uncertainty. It provides an overview of the methods and the key assumptions that allow for adaptation to different models and real world applications. The models are highly attractive due to their compactness and comprehensibility but learning their structure is computationally intensive. To combat this problem, the authors review the use of functional gradients for boosting the structure and the parameters of statistical relational models. The algorithms have been applied successfully in several SRL settings and have been adapted to several real problems from Information extraction in text to medical problems. Including both context and well-tested applications, Boosting Statistical Relational Learning from Benchmarks to Data-Driven Medicine is designed for researchers and professionals in machine learning and data mining. Computer engineers or students interested in statistics, data management, or health informatics will also find this brief a valuable resource.


Boosted Statistical Relational Learners Related Books

Boosted Statistical Relational Learners
Language: en
Pages: 79
Authors: Sriraam Natarajan
Categories: Computers
Type: BOOK - Published: 2015-03-03 - Publisher: Springer

DOWNLOAD EBOOK

This SpringerBrief addresses the challenges of analyzing multi-relational and noisy data by proposing several Statistical Relational Learning (SRL) methods. The
Introduction to Statistical Relational Learning
Language: en
Pages: 602
Authors: Lise Getoor
Categories: Computer algorithms
Type: BOOK - Published: 2007 - Publisher: MIT Press

DOWNLOAD EBOOK

In 'Introduction to Statistical Relational Learning', leading researchers in this emerging area of machine learning describe current formalisms, models, and alg
Efficient Learning of Statistical Relational Models
Language: en
Pages: 198
Authors:
Categories:
Type: BOOK - Published: 2014 - Publisher:

DOWNLOAD EBOOK

Machine Learning has been successfully applied to many prediction problems in varying domains. But standard techniques assume that the examples are independent
An Introduction to Lifted Probabilistic Inference
Language: en
Pages: 455
Authors: Guy Van den Broeck
Categories: Computers
Type: BOOK - Published: 2021-08-17 - Publisher: MIT Press

DOWNLOAD EBOOK

Recent advances in the area of lifted inference, which exploits the structure inherent in relational probabilistic models. Statistical relational AI (StaRAI) st
Ensemble Methods for Machine Learning
Language: en
Pages: 350
Authors: Gautam Kunapuli
Categories: Computers
Type: BOOK - Published: 2023-05-30 - Publisher: Simon and Schuster

DOWNLOAD EBOOK

Ensemble machine learning combines the power of multiple machine learning approaches, working together to deliver models that are highly performant and highly a