Editors:
- Offers new challenges and methods on reinforcement learning and deep reinforcement learning applied to human body motion and intelligent conversational settings
- Discusses machine learning methods for classifying clinically actionable genetic mutations
- Provides challenges and methods on adversarial learning applied to attacks and defenses
- Presents deep learning applied to transfer knowledge in art
Part of the book series: The Springer Series on Challenges in Machine Learning (SSCML)
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Table of contents (13 papers)
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Front Matter
About this book
This book summarizes the organized competitions held during the first NIPS competition track. It provides both theory and applications of hot topics in machine learning, such as adversarial learning, conversational intelligence, and deep reinforcement learning.
Rigorous competition evaluation was based on the quality of data, problem interest and impact, promoting the design of new models, and a proper schedule and management procedure. This book contains the chapters from organizers on competition design and from top-ranked participants on their proposed solutions for the five accepted competitions: The Conversational Intelligence Challenge, Classifying Clinically Actionable Genetic Mutations, Learning to Run, Human-Computer Question Answering Competition, and Adversarial Attacks and Defenses.
Editors and Affiliations
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Department Mathematics & Informatics, University of Barcelona, Barcelona, Spain
Sergio Escalera
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Microsoft (United States), Redmond, USA
Markus Weimer
Bibliographic Information
Book Title: The NIPS '17 Competition: Building Intelligent Systems
Editors: Sergio Escalera, Markus Weimer
Series Title: The Springer Series on Challenges in Machine Learning
DOI: https://doi.org/10.1007/978-3-319-94042-7
Publisher: Springer Cham
eBook Packages: Computer Science, Computer Science (R0)
Copyright Information: Springer International Publishing AG, part of Springer Nature 2018
Hardcover ISBN: 978-3-319-94041-0Published: 28 September 2018
Softcover ISBN: 978-3-030-06867-7Published: 13 December 2018
eBook ISBN: 978-3-319-94042-7Published: 27 September 2018
Series ISSN: 2520-131X
Series E-ISSN: 2520-1328
Edition Number: 1
Number of Pages: X, 287
Number of Illustrations: 85 b/w illustrations
Topics: Artificial Intelligence, Image Processing and Computer Vision, Pattern Recognition