Towards Integrative Machine Learning and Knowledge Extraction

BIRS Workshop, Banff, AB, Canada, July 24-26, 2015, Revised Selected Papers

Nonfiction, Computers, Advanced Computing, Artificial Intelligence, General Computing, Internet
Cover of the book Towards Integrative Machine Learning and Knowledge Extraction by , Springer International Publishing
View on Amazon View on AbeBooks View on Kobo View on B.Depository View on eBay View on Walmart
Author: ISBN: 9783319697758
Publisher: Springer International Publishing Publication: October 27, 2017
Imprint: Springer Language: English
Author:
ISBN: 9783319697758
Publisher: Springer International Publishing
Publication: October 27, 2017
Imprint: Springer
Language: English

The BIRS Workshop “Advances in Interactive Knowledge Discovery and Data Mining in Complex and Big Data Sets” (15w2181), held in July 2015 in Banff, Canada, was dedicated to stimulating a cross-domain integrative machine-learning approach and appraisal of “hot topics” toward tackling the grand challenge of reaching a level of useful and useable computational intelligence with a focus on real-world problems, such as in the health domain. This encompasses learning from prior data, extracting and discovering knowledge, generalizing the results, fighting the curse of dimensionality, and ultimately disentangling the underlying explanatory factors in complex data, i.e., to make sense of data within the context of the application domain. 

The workshop aimed to contribute advancements in promising novel areas such as at the intersection of machine learning and topological data analysis. History has shown that most often the overlapping areas at intersections of seemingly disparate fields are key for the stimulation of new insights and further advances. This is particularly true for the extremely broad field of machine learning.

View on Amazon View on AbeBooks View on Kobo View on B.Depository View on eBay View on Walmart

The BIRS Workshop “Advances in Interactive Knowledge Discovery and Data Mining in Complex and Big Data Sets” (15w2181), held in July 2015 in Banff, Canada, was dedicated to stimulating a cross-domain integrative machine-learning approach and appraisal of “hot topics” toward tackling the grand challenge of reaching a level of useful and useable computational intelligence with a focus on real-world problems, such as in the health domain. This encompasses learning from prior data, extracting and discovering knowledge, generalizing the results, fighting the curse of dimensionality, and ultimately disentangling the underlying explanatory factors in complex data, i.e., to make sense of data within the context of the application domain. 

The workshop aimed to contribute advancements in promising novel areas such as at the intersection of machine learning and topological data analysis. History has shown that most often the overlapping areas at intersections of seemingly disparate fields are key for the stimulation of new insights and further advances. This is particularly true for the extremely broad field of machine learning.

More books from Springer International Publishing

Cover of the book Fractional and Multivariable Calculus by
Cover of the book Islam and Health Policies Related to HIV Prevention in Malaysia by
Cover of the book Entrepreneurial Innovation and Leadership by
Cover of the book Advances in Robot Kinematics 2016 by
Cover of the book Physical Asset Management by
Cover of the book The Innovation in Computing Companion by
Cover of the book Architecture of Computing Systems – ARCS 2019 by
Cover of the book ROMANSY 21 - Robot Design, Dynamics and Control by
Cover of the book Requirements Engineering: Foundation for Software Quality by
Cover of the book Regulating Global Security by
Cover of the book An Algebraic Approach to Geometry by
Cover of the book Current Approach to Heart Failure by
Cover of the book Manual of 3D Echocardiography by
Cover of the book The Soils of the USA by
Cover of the book Control of Magnetotransport in Quantum Billiards by
We use our own "cookies" and third party cookies to improve services and to see statistical information. By using this website, you agree to our Privacy Policy