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Home > Machine Learning and Knowledge Discovery in Databases: European Conference, ECML PKDD 2019, Würzburg, Germany, September 16–20, 2019, Proceedings, Part III > Player Vectors: Characterizing Soccer Players’ Playing Style from Match Event Streams
Machine Learning and Knowledge Discovery in Databases: European Conference, ECML PKDD 2019, Würzburg, Germany, September 16–20, 2019, Proceedings, Part III |
Ulf Brefeld; Elisa Fromont; Andreas Hotho; Arno Knobbe; Marloes Maathuis; Céline Robardet
Springer International Publishing
Machine Learning and Knowledge Discovery in Databases: European Conference, ECML PKDD 2019, Würzburg, Germany, September 16–20, 2019, Proceedings, Part III
Player Vectors: Characterizing Soccer Players’ Playing Style from Match Event Streams
Authors

Tom Decroos; Jesse Davis

ARI Id

1665252467955_5570254

Access

Not Available Free

Pages

569-584

DOI

10.1007/978-3-030-46133-1_34

Chapter URL

https://rd.springer.com/chapter/10.1007/978-3-030-46133-1_34

Table of Contents of Book
Showing 1 to 20 of 64 entries
Chapters/HeadingsAuthor(s)PagesInfo
Front Matter
i-xxviii
Front Matter
1-1
Deep Ordinal Reinforcement Learning
Alexander Zap; Tobias Joppen; Johannes Fürnkranz
3-18
Sample-Efficient Model-Free Reinforcement Learning with Off-Policy Critics
Denis Steckelmacher; Hélène Plisnier; Diederik M. Roijers; Ann Nowé
19-34
Learning 3D Navigation Protocols on Touch Interfaces with Cooperative Multi-agent Reinforcement Learning
Quentin Debard; Jilles Steeve Dibangoye; Stéphane Canu; Christian Wolf
35-52
Safe Policy Improvement with Soft Baseline Bootstrapping
Kimia Nadjahi; Romain Laroche; Rémi Tachet des Combes
53-68
Practical Open-Loop Optimistic Planning
Edouard Leurent; Odalric-Ambrym Maillard
69-85
An Engineered Empirical Bernstein Bound
Mark A. Burgess; Archie C. Chapman; Paul Scott
86-102
Stochastic Activation Actor Critic Methods
Wenling Shang; Douwe van der Wal; Herke van Hoof; Max Welling
103-117
Policy Prediction Network: Model-Free Behavior Policy with Model-Based Learning in Continuous Action Space
Zac Wellmer; James T. Kwok
118-133
Attentive Multi-task Deep Reinforcement Learning
Timo Bräm; Gino Brunner; Oliver Richter; Roger Wattenhofer
134-149
Stochastic One-Sided Full-Information Bandit
Haoyu Zhao; Wei Chen
150-166
BelMan: An Information-Geometric Approach to Stochastic Bandits
Debabrota Basu; Pierre Senellart; Stéphane Bressan
167-183
Front Matter
185-185
A Ranking Model Motivated by Nonnegative Matrix Factorization with Applications to Tennis Tournaments
Rui Xia; Vincent Y. F. Tan; Louis Filstroff; Cédric Févotte
187-203
A Reduction of Label Ranking to Multiclass Classification
Klaus Brinker; Eyke Hüllermeier
204-219
Learning to Calibrate and Rerank Multi-label Predictions
Cheng Li; Virgil Pavlu; Javed Aslam; Bingyu Wang; Kechen Qin
220-236
Pairwise Learning to Rank by Neural Networks Revisited: Reconstruction, Theoretical Analysis and Practical Performance
Marius Köppel; Alexander Segner; Martin Wagener; Lukas Pensel; Andreas Karwath; Stefan Kramer
237-252
Sequential Learning over Implicit Feedback for Robust Large-Scale Recommender Systems
Aleksandra Burashnikova; Yury Maximov; Massih-Reza Amini
253-269
Front Matter
271-271
Chapters/HeadingsAuthor(s)PagesInfo
Showing 1 to 20 of 64 entries
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