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The NIPS '17 Competition: Building Intelligent Systems

  • Sergio Escalera
  • Markus Weimer

Table of contents

  1. Front Matter
    Pages i-x
  2. Sergio Escalera, Markus Weimer, Mikhail Burtsev, Valentin Malykh, Varvara Logacheva, Ryan Lowe et al.
    Pages 1-23
  3. Mikhail Burtsev, Varvara Logacheva, Valentin Malykh, Iulian Vlad Serban, Ryan Lowe, Shrimai Prabhumoye et al.
    Pages 25-46
  4. Varvara Logacheva, Mikhail Burtsev, Valentin Malykh, Vadim Polulyakh, Aleksandr Seliverstov
    Pages 47-57
  5. Jan Chorowski, Adrian Lancucki, Szymon Malik, Maciej Pawlikowski, Pawel Rychlikowski, Pawel Zykowski
    Pages 59-77
  6. Xi Zhang, Dandi Chen, Yongjun Zhu, Chao Che, Chang Su, Sendong Zhao et al.
    Pages 79-99
  7. Łukasz Kidziński, Sharada P. Mohanty, Carmichael F. Ong, Jennifer L. Hicks, Sean F. Carroll, Sergey Levine et al.
    Pages 101-120
  8. Łukasz Kidziński, Sharada Prasanna Mohanty, Carmichael F. Ong, Zhewei Huang, Shuchang Zhou, Anton Pechenko et al.
    Pages 121-153
  9. Wojciech Jaśkowski, Odd Rune Lykkebø, Nihat Engin Toklu, Florian Trifterer, Zdeněk Buk, Jan Koutník et al.
    Pages 155-167
  10. Jordan Boyd-Graber, Shi Feng, Pedro Rodriguez
    Pages 169-180
  11. Ikuya Yamada, Ryuji Tamaki, Hiroyuki Shindo, Yoshiyasu Takefuji
    Pages 181-194
  12. Alexey Kurakin, Ian Goodfellow, Samy Bengio, Yinpeng Dong, Fangzhou Liao, Ming Liang et al.
    Pages 195-231
  13. David Benrimoh, Robert Fratila, Sonia Israel, Kelly Perlman, Nykan Mirchi, Sneha Desai et al.
    Pages 251-287

About these proceedings

Introduction

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.

Keywords

deep learning reinforcement learning neural information processing systems adversarial learning deep reinforcement learning conversational settings natural language processing chatbots genetic mutations intelligent agents computer vision machine learning

Editors and affiliations

  • Sergio Escalera
    • 1
  • Markus Weimer
    • 2
  1. 1.Department Mathematics & InformaticsUniversity of BarcelonaBarcelonaSpain
  2. 2.Microsoft (United States)RedmondUSA

Bibliographic information

  • DOI https://doi.org/10.1007/978-3-319-94042-7
  • Copyright Information Springer International Publishing AG, part of Springer Nature 2018
  • Publisher Name Springer, Cham
  • eBook Packages Computer Science
  • Print ISBN 978-3-319-94041-0
  • Online ISBN 978-3-319-94042-7
  • Series Print ISSN 2520-131X
  • Series Online ISSN 2520-1328
  • Buy this book on publisher's site