Overview
- Includes supplementary material: sn.pub/extras
Part of the book series: Lecture Notes in Computer Science (LNCS, volume 10344)
Part of the book sub series: Lecture Notes in Artificial Intelligence (LNAI)
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Table of contents (12 papers)
Keywords
- artificial intelligence
- bioinformatics
- brain tumor
- classification
- data mining
- decision trees
- deep learning
- digital pathology
- health informatics
- image processing
- information theory
- integrative machine learning
- knowledge extraction
- learning algorithms
- persistent homology
- predictive models
- probabilistic logic progamming
About this book
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.
Editors and Affiliations
Bibliographic Information
Book Title: Towards Integrative Machine Learning and Knowledge Extraction
Book Subtitle: BIRS Workshop, Banff, AB, Canada, July 24-26, 2015, Revised Selected Papers
Editors: Andreas Holzinger, Randy Goebel, Massimo Ferri, Vasile Palade
Series Title: Lecture Notes in Computer Science
DOI: https://doi.org/10.1007/978-3-319-69775-8
Publisher: Springer Cham
eBook Packages: Computer Science, Computer Science (R0)
Copyright Information: Springer International Publishing AG 2017
Softcover ISBN: 978-3-319-69774-1Published: 29 October 2017
eBook ISBN: 978-3-319-69775-8Published: 27 October 2017
Series ISSN: 0302-9743
Series E-ISSN: 1611-3349
Edition Number: 1
Number of Pages: XVI, 207
Number of Illustrations: 57 b/w illustrations
Topics: Artificial Intelligence, Information Systems and Communication Service, Probability and Statistics in Computer Science, Software Engineering/Programming and Operating Systems, Computer Systems Organization and Communication Networks