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Introduction to Semi-Supervised Learning
Semi-supervised learning is a learning paradigm concerned with the study of how computers and natural systems such as humans learn in the presence of both labeled and unlabeled data. Traditionally, learning has been studied either in the unsupervised paradigm (e.g., clustering, outlier detection) where all the data are unlabeled, or in the supervised paradigm (e.g., classification, regression) where all the data are labeled. The goal of semi-supervised learning is to understand how combining labeled and unlabeled data may change the learning behavior, and design algorithms that take advantage of such a combination. Semi-supervised learning is of great interest in machine learning and data mi...
Machine Learning: ECML 2005
This book constitutes the refereed proceedings of the 16th European Conference on Machine Learning, ECML 2005, jointly held with PKDD 2005 in Porto, Portugal, in October 2005. The 40 revised full papers and 32 revised short papers presented together with abstracts of 6 invited talks were carefully reviewed and selected from 335 papers submitted to ECML and 30 papers submitted to both, ECML and PKDD. The papers present a wealth of new results in the area and address all current issues in machine learning.
Machine Learning and Knowledge Discovery in Databases. Applied Data Science Track
The multi-volume set LNAI 12975 until 12979 constitutes the refereed proceedings of the European Conference on Machine Learning and Knowledge Discovery in Databases, ECML PKDD 2021, which was held during September 13-17, 2021. The conference was originally planned to take place in Bilbao, Spain, but changed to an online event due to the COVID-19 pandemic. The 210 full papers presented in these proceedings were carefully reviewed and selected from a total of 869 submissions. The volumes are organized in topical sections as follows: Research Track: Part I: Online learning; reinforcement learning; time series, streams, and sequence models; transfer and multi-task learning; semi-supervised and f...
Machine Learning: ECML 2003
This book constitutes the refereed proceedings of the 14th European Conference on Machine Learning, ECML 2003, held in Cavtat-Dubrovnik, Croatia in September 2003 in conjunction with PKDD 2003. The 40 revised full papers presented together with 4 invited contributions were carefully reviewed and, together with another 40 ones for PKDD 2003, selected from a total of 332 submissions. The papers address all current issues in machine learning including support vector machine, inductive inference, feature selection algorithms, reinforcement learning, preference learning, probabilistic grammatical inference, decision tree learning, clustering, classification, agent learning, Markov networks, boosting, statistical parsing, Bayesian learning, supervised learning, and multi-instance learning.
Machine Learning and Knowledge Discovery in Databases. Research Track
The multi-volume set LNAI 12975 until 12979 constitutes the refereed proceedings of the European Conference on Machine Learning and Knowledge Discovery in Databases, ECML PKDD 2021, which was held during September 13-17, 2021. The conference was originally planned to take place in Bilbao, Spain, but changed to an online event due to the COVID-19 pandemic. The 210 full papers presented in these proceedings were carefully reviewed and selected from a total of 869 submissions. The volumes are organized in topical sections as follows: Research Track: Part I: Online learning; reinforcement learning; time series, streams, and sequence models; transfer and multi-task learning; semi-supervised and f...
13th World Congress of Performance Analysis of Sport and 13th International Symposium on Computer Science in Sport
This book discovers the latest research and insights in sports performance analysis and computer science in sports with the 13th World Congress of Performance Analysis of Sport and 13th International Symposium on Computer Science in Sport joint conference proceedings. This comprehensive book features over 40 peer-reviewed scientific works, showcasing the latest developments in these areas. The book covers a wide range of topics, including data analytics in sports, performance tracking and monitoring, artificial intelligence and machine learning in sports, virtual and augmented reality in sports, sensor technology, sports biomechanics, and motor control. By reading this book, you'll gain a deeper understanding of how applied and research-based problems can, together, transform the world of sports, and how you can stay ahead of the curve in this rapidly evolving field. This means that whether you're a researcher, coach, athlete, or sports enthusiast, there is something for everyone in this book.
HCI International 2020 - Posters
The three-volume set CCIS 1224, CCIS 1225, and CCIS 1226 contains the extended abstracts of the posters presented during the 22nd International Conference on Human-Computer Interaction, HCII 2020, which took place in Copenhagen, Denmark, in July 2020.* HCII 2020 received a total of 6326 submissions, of which 1439 papers and 238 posters were accepted for publication in the pre-conference proceedings after a careful reviewing process. The 238 papers presented in these three volumes are organized in topical sections as follows: Part I: design and evaluation methods and tools; user characteristics, requirements and preferences; multimodal and natural interaction; recognizing human psychological ...
