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Machine Learning and Principles and Practice of Knowledge Discovery in Databases : International Workshops of ECML PKDD 2022, Grenoble, France, September 19–23, 2022, Proceedings, Part II / edited by Irena Koprinska, Paolo Mignone, Riccardo Guidotti, Szymon Jaroszewicz, Holger Fröning, Francesco Gullo, Pedro M. Ferreira, Damian Roqueiro, Gaia Ceddia, Slawomir Nowaczyk, João Gama, Rita Ribeiro, Ricard Gavaldà, Elio Masciari, Zbigniew Ras, Ettore Ritacco, Francesca Naretto, Andreas Theissler, Przemyslaw Biecek, Wouter Verbeke, Gregor Schiele, Franz Pernkopf, Michaela Blott, Ilaria Bordino, Ivan Luciano Danesi, Giovanni Ponti, Lorenzo Severini, Annalisa Appice, Giuseppina Andresini, Ibéria Medeiros, Guilherme Graça, Lee Cooper, Naghmeh Ghazaleh, Jonas Richiardi, Diego Saldana, Konstantinos Sechidis, Arif Canakoglu, Sara Pido, Pietro Pinoli, Albert Bifet, Sepideh Pashami
(Communications in Computer and Information Science. ISSN:18650937 ; 1753)
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| 一般注記 | Workshop on Mining Data for Financial Application (MIDAS 2022) -- Preface from the workshop organisers -- Multi-Task Learning for Features Extraction in Financial Annual Reports -- What to do with your sentiments in finance -- On the development of a European tracker of societal issues and economic activities using alternative data -- Privacy-preserving machine learning in life insurance risk prediction -- Financial Distress Model Prediction using Machine Learning: A Case Study on Indonesia’s Consumers Cyclical Companies -- Improve default prediction in highly unbalanced context -- Towards Explainable Occupational Fraud Detection -- Towards Data-Driven Volatility Modeling with Variational Autoencoders -- Auto-Clustering of Financial Reports Based on Formatting Style and Author’s Fingerprint -- InFi-BERT 1.0: Transformer-based language model for Indian Financial Volatility Prediction -- Workshop on Machine Learning for Cybersecurity (MLCS 2022) -- Preface from the workshop organisers -- Intrusion Detection using Ensemble Models -- Domain Adaptation with Maximum Margin Criterion with application to network traffic classification -- Evaluation of Detection Limit in Network Dataset Quality Assessment with Permutation Testing -- Towards a General Model for Intrusion Detection: An Exploratory Study -- Workshop on Machine Learning for Buildings Energy Management (MLBEM 2022) -- Preface from the workshop organisers -- Conv-NILM-Net, a causal and multi-appliance model for energy source separation -- Domestic Hot Water Forecasting for Individual Housing with Deep Learning -- Workshop on Machine Learning for Pharma and Healthcare Applications (PharML 2022) -- Preface from the workshop organisers -- Detecting Drift in Healthcare AI Models based on Data Availability -- Assessing Different Feature Selection Methods applied to a bulk RNA Sequencing Dataset with regard to Biomedical Relevance -- Predicting Drug Treatment for Hospitalized Patients with Heart Failure -- A Workflow for Generating Patient Counterfactuals in Lung Transplant Recipients -- Few-Shot Learning for Identification of COVID-19 Symptoms Using Generative Pre-Trained Transformer Language Models -- A Light-weight Deep Residual Network for Classification of Abnormal Heart Rhythms on Tiny Devices -- Workshop on Data Analysis in Life Science (DALS 2022) -- Preface from the workshop organisers -- I-CONVEX: Fast and Accurate de Novo Transcriptome Recovery from Long Reads -- Italian debate on measles vaccination: how Twitter data highlight communities and polarity -- Workshop on IoT Streams for Predictive Maintenance (IoT-PdM 2022) -- Preface from the workshop organisers -- Online Anomaly Explanation: A Case Study on Predictive Maintenance -- Fault forecasting using data-driven system modeling: a case study for Metro do Porto data set -- An online data-driven predictive maintenance approach for railway switches -- curr2vib: Modality Embedding Translation for Broken-Rotor Bar Detection -- Incorporating Physics-based Models into Data-Driven Approaches for Air Leak Detection in City Buses -- Towards Geometry-Preserving Domain Adaptation for Fault Identification -- A systematic approach for tracking the evolution of XAI as a field of research -- Frequent Generalized Subgraph Mining via Graph Edit Distances. This volume constitutes the papers of several workshops which were held in conjunction with the International Workshops of ECML PKDD 2022 on Machine Learning and Principles and Practice of Knowledge Discovery in Databases, ECML PKDD 2022, held in Grenoble, France, during September 19–23, 2022. The 73 revised full papers and 6 short papers presented in this book were carefully reviewed and selected from 143 submissions. ECML PKDD 2022 presents the following five workshops: Workshop on Data Science for Social Good (SoGood 2022) Workshop on New Frontiers in Mining Complex Patterns (NFMCP 2022) Workshop on Explainable Knowledge Discovery in Data Mining (XKDD 2022) Workshop on Uplift Modeling (UMOD 2022) Workshop on IoT, Edge and Mobile for Embedded Machine Learning (ITEM 2022) Workshop on Mining Data for Financial Application (MIDAS 2022) Workshop on Machine Learning for Cybersecurity (MLCS 2022) Workshop on Machine Learning for Buildings Energy Management (MLBEM 2022) Workshop on Machine Learning for Pharma and Healthcare Applications (PharML 2022) Workshop on Data Analysis in Life Science (DALS 2022) Workshop on IoT Streams for Predictive Maintenance (IoT-PdM 2022) HTTP:URL=https://doi.org/10.1007/978-3-031-23633-4 |
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| 件 名 | LCSH:Artificial intelligence LCSH:Computer networks LCSH:Social sciences -- Data processing 全ての件名で検索 LCSH:Application software LCSH:Education -- Data processing 全ての件名で検索 FREE:Artificial Intelligence FREE:Computer Communication Networks FREE:Computer Application in Social and Behavioral Sciences FREE:Computer and Information Systems Applications FREE:Computers and Education |
| 分 類 | LCC:Q334-342 LCC:TA347.A78 DC23:006.3 |
| 書誌ID | EB00004256 |
| ISBN | 9783031236334 |
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