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Showing 1 - 7 of
7 matches in All Departments
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Machine Learning and Data Mining for Sports Analytics - 8th International Workshop, MLSA 2021, Virtual Event, September 13, 2021, Revised Selected Papers (Paperback, 1st ed. 2022)
Ulf Brefeld, Jesse Davis, Jan Van Haaren, Albrecht Zimmermann
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R2,461
Discovery Miles 24 610
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Ships in 10 - 15 working days
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This book constitutes the refereed post-conference proceedings of
the 8th International Workshop on Machine Learning and Data Mining
for Sports Analytics, MLSA 2021, held as virtual event in September
2021. The 12 full papers and 4 short papers presented were
carefully reviewed and selected from 29 submissions. The papers
present a variety of topics within the area of sports analytics,
including tactical analysis, outcome predictions, data acquisition,
performance optimization, and player evaluation.
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Machine Learning and Data Mining for Sports Analytics - 7th International Workshop, MLSA 2020, Co-located with ECML/PKDD 2020, Ghent, Belgium, September 14-18, 2020, Proceedings (Paperback, 1st ed. 2020)
Ulf Brefeld, Jesse Davis, Jan Van Haaren, Albrecht Zimmermann
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R1,580
Discovery Miles 15 800
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Ships in 10 - 15 working days
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This book constitutes the refereed post-conference proceedings of
the 7th International Workshop on Machine Learning and Data Mining
for Sports Analytics, MLSA 2020, colocated with ECML/PKDD 2020, in
Ghent, Belgium, in September 2020. Due to the COVID-19 pandemic the
conference was held online. The 11 papers presented were carefully
reviewed and selected from 22 submissions. The papers present a
variety of topics within the area of sports analytics, including
tactical analysis, outcome predictions, data acquisition,
performance optimization, and player evaluation.
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Machine Learning and Knowledge Discovery in Databases - European Conference, ECML PKDD 2019, Wurzburg, Germany, September 16-20, 2019, Proceedings, Part III (Paperback, 1st ed. 2020)
Ulf Brefeld, Elisa Fromont, Andreas Hotho, Arno Knobbe, Marloes Maathuis, …
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R1,749
Discovery Miles 17 490
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Ships in 10 - 15 working days
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The three volume proceedings LNAI 11906 - 11908 constitutes the
refereed proceedings of the European Conference on Machine Learning
and Knowledge Discovery in Databases, ECML PKDD 2019, held in
Wurzburg, Germany, in September 2019.The total of 130 regular
papers presented in these volumes was carefully reviewed and
selected from 733 submissions; there are 10 papers in the demo
track. The contributions were organized in topical sections named
as follows: Part I: pattern mining; clustering, anomaly and outlier
detection, and autoencoders; dimensionality reduction and feature
selection; social networks and graphs; decision trees,
interpretability, and causality; strings and streams; privacy and
security; optimization. Part II: supervised learning; multi-label
learning; large-scale learning; deep learning; probabilistic
models; natural language processing. Part III: reinforcement
learning and bandits; ranking; applied data science: computer
vision and explanation; applied data science: healthcare; applied
data science: e-commerce, finance, and advertising; applied data
science: rich data; applied data science: applications; demo track.
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Machine Learning and Knowledge Discovery in Databases - European Conference, ECML PKDD 2019, Wurzburg, Germany, September 16-20, 2019, Proceedings, Part II (Paperback, 1st ed. 2020)
Ulf Brefeld, Elisa Fromont, Andreas Hotho, Arno Knobbe, Marloes Maathuis, …
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R3,150
Discovery Miles 31 500
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Ships in 10 - 15 working days
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The three volume proceedings LNAI 11906 - 11908 constitutes the
refereed proceedings of the European Conference on Machine Learning
and Knowledge Discovery in Databases, ECML PKDD 2019, held in
Wurzburg, Germany, in September 2019.The total of 130 regular
papers presented in these volumes was carefully reviewed and
selected from 733 submissions; there are 10 papers in the demo
track. The contributions were organized in topical sections named
as follows: Part I: pattern mining; clustering, anomaly and outlier
detection, and autoencoders; dimensionality reduction and feature
selection; social networks and graphs; decision trees,
interpretability, and causality; strings and streams; privacy and
security; optimization. Part II: supervised learning; multi-label
learning; large-scale learning; deep learning; probabilistic
models; natural language processing. Part III: reinforcement
learning and bandits; ranking; applied data science: computer
vision and explanation; applied data science: healthcare; applied
data science: e-commerce, finance, and advertising; applied data
science: rich data; applied data science: applications; demo track.
Chapter "Incorporating Dependencies in Spectral Kernels for
Gaussian Processes" is available open access under a Creative
Commons Attribution 4.0 International License via
link.springer.com.
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Machine Learning and Knowledge Discovery in Databases - European Conference, ECML PKDD 2019, Wurzburg, Germany, September 16-20, 2019, Proceedings, Part I (Paperback, 1st ed. 2020)
Ulf Brefeld, Elisa Fromont, Andreas Hotho, Arno Knobbe, Marloes Maathuis, …
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R3,168
Discovery Miles 31 680
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Ships in 10 - 15 working days
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The three volume proceedings LNAI 11906 - 11908 constitutes the
refereed proceedings of the European Conference on Machine Learning
and Knowledge Discovery in Databases, ECML PKDD 2019, held in
Wurzburg, Germany, in September 2019.The total of 130 regular
papers presented in these volumes was carefully reviewed and
selected from 733 submissions; there are 10 papers in the demo
track. The contributions were organized in topical sections named
as follows: Part I: pattern mining; clustering, anomaly and outlier
detection, and autoencoders; dimensionality reduction and feature
selection; social networks and graphs; decision trees,
interpretability, and causality; strings and streams; privacy and
security; optimization. Part II: supervised learning; multi-label
learning; large-scale learning; deep learning; probabilistic
models; natural language processing. Part III: reinforcement
learning and bandits; ranking; applied data science: computer
vision and explanation; applied data science: healthcare; applied
data science: e-commerce, finance, and advertising; applied data
science: rich data; applied data science: applications; demo track.
Chapter "Heavy-tailed Kernels Reveal a Finer Cluster Structure in
t-SNE Visualisations" is available open access under a Creative
Commons Attribution 4.0 International License via
link.springer.com.
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Machine Learning and Data Mining for Sports Analytics - 5th International Workshop, MLSA 2018, Co-located with ECML/PKDD 2018, Dublin, Ireland, September 10, 2018, Proceedings (Paperback, 1st ed. 2019)
Ulf Brefeld, Jesse Davis, Jan Van Haaren, Albrecht Zimmermann
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R1,839
Discovery Miles 18 390
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Ships in 10 - 15 working days
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This book constitutes the refereed post-conference proceedings of
the 5th International Workshop on Machine Learning and Data Mining
for Sports Analytics, MLSA 2018, colocated with ECML/PKDD 2018, in
Dublin, Ireland, in September 2018. The 12 full papers presented
together with 4 challenge papers were carefully reviewed and
selected from 24 submissions. The papers present a variety of
topics, covering the team sports American football, basketball, ice
hockey, and soccer, as well as the individual sports cycling and
martial arts. In addition, four challenge papers are included,
reporting on how to predict pass receivers in soccer.
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Machine Learning and Knowledge Discovery in Databases - European Conference, ECML PKDD 2018, Dublin, Ireland, September 10-14, 2018, Proceedings, Part III (Paperback, 1st ed. 2019)
Ulf Brefeld, Edward Curry, Elizabeth Daly, Brian MacNamee, Alice Marascu, …
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R1,721
Discovery Miles 17 210
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Ships in 10 - 15 working days
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The three volume proceedings LNAI 11051 - 11053 constitutes the
refereed proceedings of the European Conference on Machine Learning
and Knowledge Discovery in Databases, ECML PKDD 2018, held in
Dublin, Ireland, in September 2018. The total of 131 regular papers
presented in part I and part II was carefully reviewed and selected
from 535 submissions; there are 52 papers in the applied data
science, nectar and demo track. The contributions were organized in
topical sections named as follows: Part I: adversarial learning;
anomaly and outlier detection; applications; classification;
clustering and unsupervised learning; deep learning; ensemble
methods; and evaluation. Part II: graphs; kernel methods; learning
paradigms; matrix and tensor analysis; online and active learning;
pattern and sequence mining; probabilistic models and statistical
methods; recommender systems; and transfer learning. Part III: ADS
data science applications; ADS e-commerce; ADS engineering and
design; ADS financial and security; ADS health; ADS sensing and
positioning; nectar track; and demo track.
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