The NIPS '17 Competition: Building Intelligent Systems

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.

Summary

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.

Product details

• Assisted by: Sergi Escalera (Editor), Sergio Escalera (Editor), Weimer (Editor), Weimer (Editor), Markus Weimer (Editor)
• Publisher: Springer, Berlin
• Languages: English
• Product format: Hardback
• Released: 01.01.2018
• EAN: 9783319940410
• ISBN: 978-3-31-994041-0
• No. of pages: 287
• Dimensions: 166 mm x 243 mm x 23 mm
• Weight: 596 g
• Illustrations: X, 287 p. 85 illus.
• Series: The Springer Series on Challenges in Machine Learning; The Springer Series on Challenges in Machine Learning
• Subjects: Natural sciences, medicine, IT, technology > IT, data processing > IT; C, machine learning, Artificial Intelligence, Mustererkennung, Maschinelles Sehen, Bildverstehen, computer science, Computer Vision, Image Processing and Computer Vision, pattern recognition, Automated Pattern Recognition, Optical data processing, Image processing, Intelligent Agents