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Advances in Intelligent Data Analysis XX: 20th International Symposium on Intelligent Data Analysis, IDA 2022, Rennes, France, April 20–22, 2022, Proceedings de Tassadit Bouadi

Advances in Intelligent Data Analysis XX: 20th International Symposium on Intelligent Data Analysis, IDA 2022, Rennes, France, April 20–22, 2022, Proceedings: Lecture Notes in Computer Science, cartea 13205

Editat de Tassadit Bouadi, Elisa Fromont, Eyke Hüllermeier
en Limba Engleză Paperback – 7 apr 2022
This book constitutes the proceedings of the 20th International Symposium on Intelligent Data Analysis, IDA 2022, which was held in Rennes, France, during April 20-22, 2022.  The 31 papers included in this book were carefully reviewed and selected from 73 submissions. They deal with high quality, novel research in intelligent data analysis. 
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Specificații

ISBN-13: 9783031013324
ISBN-10: 3031013328
Pagini: 406
Ilustrații: XIII, 406 p. 126 illus., 101 illus. in color.
Dimensiuni: 155 x 235 mm
Greutate: 0.59 kg
Ediția:1st ed. 2022
Editura: Springer International Publishing
Colecția Springer
Seria Lecture Notes in Computer Science

Locul publicării:Cham, Switzerland

Cuprins

Multi-Modal Ensembles of Regressor Chains for Multi-Output Prediction.- A Two-Step Approach for Explainable Relation Extraction.- Towards Automation of Topic Taxonomy Construction.- A fault detection framework based on LSTM autoencoder: a case study for Volvo bus data.- Detection and Multi-Label Classification of Bats.- End-to-End Mobile System for Diabetic Retinopathy Screening Based on Lightweight Deep Neural Network.- Effcient Bayesian learning of sparse deep artificial neural networks.- Tensor Completion Post-Correction.- Hadi Fanaee-T S-LIME: Reconciling Locality and Fidelity in Linear Explanations.- Changes in Predictions of Classification Models for Data Streams.- Impact of dimensionality on nowcasting seasonal influenza with environmental factors.- On Usefulness of Outlier Elimination in Classification Tasks.- Suitability of Different Metric Choices for Concept Drift Detection.- Exploring the Geometry and Topology of Neural Network Loss Landscapes.- Selecting Outstanding Patterns Based on their Neighbourhood.- Using Explainable Boosting Machine to Compare Idiographic and Nomothetic Approaches for Ecological Momentary Assessment Data.- dunXai: DO-U-Net for Explainable (Multi-Label) Image Classification.- AGS: Attribution Guided Sharpening as a Defense Against Adversarial Attacks.- VAE-CE: Visual Contrastive Explanation using Disentangled VAEs.- Evaluation of Uplift Models with Non-Random Assignment Bias.- A Generic Trace Ordering Framework for Incremental Process Discovery.- Bank statements to network features: Extracting features out of time series using visibility graph.- Modular-Relatedness for Continual Learning.- Combining Multiple Data Sources to Predict IUCN Conservation Status of Reptiles.- LG4AV: Combining Language Models and Graph Neural Networks for Author Verification.-Effcient Subgroup Discovery Through Auto-Encoding.- Simulation of scientific experiments with generative models.- A Learning Vector Quantization Architecture for Transfer Learning Based Classification in Case of Multiple Sources by Means of Nullspace Evaluation.- MuseBar: Alleviating Posterior Collapse in Recurrent VAEs toward Music Generation.- Parameter Learning in ProbLog With Annotated Disjunctions.- Semantic-Based Few-Shot Classification by Psychometric Learning.