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

Machine learning and principles and practice of knowledge discovery in databases : Part II / international workshops of ECML PKDD 2022, Grenoble, France, September 19-23, 2022 : proceedings. Irena Koprinska, Paolo Mignone, Riccardo Guidotti, Szymon Jaroszewicz, Holger Fröning, Francesco Gullo, Pedro M. Ferreira, Damian Roqueiro et al. (eds.).

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書目詳細資料
企業作者: ECML PKDD (Conference) Grenoble, France)
其他作者: Koprinska, Irena (Editor)
格式: 電子書
語言:English
出版: Cham : Springer, [2023]
叢編:Communications in computer and information science ; 1753.
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Machine learning > Congresses.
Data mining > Congresses.
Data mining
Machine learning
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proceedings (reports)
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Conference papers and proceedings.
Actes de congrès.
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書本目錄:
  • 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. .

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