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 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 II / [electronic resource] :
edited by Michael Kamp, Irena Koprinska, Adrien Bibal, Tassadit Bouadi, Benoît Frénay, Luis Galárraga, José Oramas, Linara Adilova, Yamuna Krishnamurthy, Bo Kang, Christine Largeron, Jefrey Lijffijt, Tiphaine Viard, Pascal Welke, Massimiliano Ruocco, Erlend Aune, Claudio Gallicchio, Gregor Schiele, Franz Pernkopf, Michaela Blott, Holger Fröning, Günther Schindler, Riccardo Guidotti, Anna Monreale, Salvatore Rinzivillo, Przemyslaw Biecek, Eirini Ntoutsi, Mykola Pechenizkiy, Bodo Rosenhahn, Christopher Buckley, Daniela Cialfi, Pablo Lanillos, Maxwell Ramstead, Tim Verbelen, Pedro M. Ferreira, Giuseppina Andresini, Donato Malerba, Ibéria Medeiros, Philippe Fournier-Viger, M. Saqib Nawaz, Sebastian Ventura, Meng Sun, Min Zhou, Valerio Bitetta, Ilaria Bordino, Andrea Ferretti, Francesco Gullo, Giovanni Ponti, Lorenzo Severini, Rita Ribeiro, João Gama, Ricard Gavaldà, Lee Cooper, Naghmeh Ghazaleh, Jonas Richiardi, Damian Roqueiro, Diego Saldana Miranda, Konstantinos Sechidis, Guilherme Graça.
- 1st ed. 2021.
- XXVI, 584 p. 156 illus., 135 illus. in color. online resource.
- Communications in Computer and Information Science, 1525 1865-0937 ; .
- Communications in Computer and Information Science, 1525 .
Machine Learning for CyberSecurity -- Workshop on Machine Learning in Softtware Engineering -- MIning DAta for financial applicationS -- Sixth Workshop on Data Science for Social Good (SoGood 2021) -- Machine Learning for Pharma and Healthcare Applications -- Machine Learning for Buildings Energy Management.
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).
9783030937331
10.1007/978-3-030-93733-1 doi
Artificial intelligence.
Computer engineering.
Computer networks .
Social sciences--Data processing.
Computers.
Image processing--Digital techniques.
Computer vision.
Artificial Intelligence.
Computer Engineering and Networks.
Computer Application in Social and Behavioral Sciences.
Computing Milieux.
Computer Engineering and Networks.
Computer Imaging, Vision, Pattern Recognition and Graphics.
Q334-342 TA347.A78
006.3
Machine Learning for CyberSecurity -- Workshop on Machine Learning in Softtware Engineering -- MIning DAta for financial applicationS -- Sixth Workshop on Data Science for Social Good (SoGood 2021) -- Machine Learning for Pharma and Healthcare Applications -- Machine Learning for Buildings Energy Management.
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).
9783030937331
10.1007/978-3-030-93733-1 doi
Artificial intelligence.
Computer engineering.
Computer networks .
Social sciences--Data processing.
Computers.
Image processing--Digital techniques.
Computer vision.
Artificial Intelligence.
Computer Engineering and Networks.
Computer Application in Social and Behavioral Sciences.
Computing Milieux.
Computer Engineering and Networks.
Computer Imaging, Vision, Pattern Recognition and Graphics.
Q334-342 TA347.A78
006.3