Christopher Buckley

Giovanni Ponti

Andrea Ferretti

Valerio Bitetta

Lorenzo Severini

Francesco Gullo

Ilaria Bordino

Ricard Gavaldà

João Gama

Donato Malerba

Min Zhou

Rita Ribeiro

Philippe Fournier-Viger

Massimiliano Ruocco

Michael Kamp

Lee Cooper

Przemyslaw Biecek

Sebastian Ventura

Mykola Pechenizkiy

Riccardo Guidotti

Anna Monreale

Christine Largeron

Jefrey Lijffijt

Irena Koprinska

Linara Adilova

Yamuna Krishnamurthy

Pedro M. Ferreira

Ibéria Medeiros

Eirini Ntoutsi

Salvatore Rinzivillo

Pablo Lanillos

Bodo Rosenhahn

Holger Fröning

Damian Roqueiro

Gregor Schiele

Franz Pernkopf

Michaela Blott

Giuseppina Andresini

Guilherme Graça

Naghmeh Ghazaleh

Jonas Richiardi

Konstantinos Sechidis

Benoît Frénay

Bo Kang

Tiphaine Viard

Pascal Welke

Erlend Aune

Claudio Gallicchio

Adrien Bibal

Tassadit Bouadi

Luis Galárraga

José Oramas

Günther Schindler

Daniela Cialfi

Maxwell Ramstead

Tim Verbelen

M. Saqib Nawaz

Meng Sun

Diego Saldana Miranda

This two-volume set constitutes the refereed proceedings of the workshops which complemented the 21th Joint European Conference on Machine Learning and Knowledge Discovery in Databases, ECML PKDD, held in September 2021. Due to the COVID-19 pandemic the conference and workshops were held online. The 104 papers were thoroughly reviewed and selected from 180 papers submited for the workshops. This two-volume set includes the proceedings of the following workshops:Workshop on Advances in Interpretable Machine Learning and Artificial Intelligence (AIMLAI 2021)Workshop on Parallel, Distributed and Federated Learning (PDFL 2021)Workshop on Graph Embedding and Mining (GEM 2021)Workshop on Machine Learning for Irregular Time-series (ML4ITS 2021)Workshop on IoT, Edge, and Mobile for Embedded Machine Learning (ITEM 2021)Workshop on eXplainable Knowledge Discovery in Data Mining (XKDD 2021)Workshop on Bias and Fairness in AI (BIAS 2021)Workshop on Workshop on Active Inference (IWAI 2021)Workshop on Machine Learning for Cybersecurity (MLCS 2021)Workshop on Machine Learning in Software Engineering (MLiSE 2021)Workshop on MIning Data for financial applications (MIDAS 2021)Sixth Workshop on Data Science for Social Good (SoGood 2021)Workshop on Machine Learning for Pharma and Healthcare Applications (PharML 2021)Second Workshop on Evaluation and Experimental Design in Data Mining and Machine Learning (EDML 2020)Workshop on Machine Learning for Buildings Energy Management (MLBEM 2021)

International Workshops of ECML PKDD 2021, Virtual Event, September 13-17, 2021, Proceedings, Part II

Machine Learning and Principles and Practice of Knowledge Discovery in Databases

International Workshops of ECML PKDD 2021, Virtual Event, September 13-17, 2021, Proceedings, Part I

Cristobal Romero

Ryan S.J.d. Baker

Handbook of Educational Data Mining (EDM) provides a thorough overview of the current state of knowledge in this area. The first part of the book includes nine surveys and tutorials on the principal data mining techniques that have been applied in education. The second part presents a set of 25 case studies that give a rich overview of the problems that EDM has addressed. Researchers at the Forefront of the Field Discuss Essential Topics and the Latest Advances With contributions by well-known researchers from a variety of fields, the book reflects the multidisciplinary nature of the EDM community. It brings the educational and data mining communities together, helping education experts understand what types of questions EDM can address and helping data miners understand what types of questions are important to educational design and educational decision making. Encouraging readers to integrate EDM into their research and practice, this timely handbook offers a broad, accessible treatment of essential EDM techniques and applications. It provides an excellent first step for newcomers to the EDM community and for active researchers to keep abreast of recent developments in the field.

Handbook of Educational Data Mining

Sebastian Ventura

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