Machine Learning and Principles and Practice of Knowledge Discovery in Databases: International Workshops of Ecml Pkdd 2021, Virtual Event, September

ISBN-13: 9783030937355 / Angielski / Miękka / 2022 / 910 str.

Kamp, Michael

Opis

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)

Spis treści

Advances in Interpretable Machine Learning and Artificial Intelligence.- Parallel, Distributed, and Federated Learning.- Graph Embedding and Mining.- Machine Learning for Irregular Time Series.-  IoT, Edge, and Mobile for Embedded Machine Learning.- eXplainable Knowledge Discovery in Data Mining.- Bias and Fairness in AI.- International Workshop on Active Inference.