Advances in Intelligent Data Analysis XX
20th International Symposium on Intelligent Data Analysis, IDA 2022, Rennes, France, April 20¿22, 2022, Proceedings
Herausgegeben:Bouadi, Tassadit; Fromont, Elisa; Hüllermeier, Eyke
Advances in Intelligent Data Analysis XX
20th International Symposium on Intelligent Data Analysis, IDA 2022, Rennes, France, April 20¿22, 2022, Proceedings
Herausgegeben:Bouadi, Tassadit; Fromont, Elisa; Hüllermeier, Eyke
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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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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.
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.
Produktdetails
- Produktdetails
- Lecture Notes in Computer Science 13205
- Verlag: Springer / Springer International Publishing / Springer, Berlin
- Artikelnr. des Verlages: 978-3-031-01332-4
- 1st ed. 2022
- Seitenzahl: 420
- Erscheinungstermin: 7. April 2022
- Englisch
- Abmessung: 235mm x 155mm x 23mm
- Gewicht: 633g
- ISBN-13: 9783031013324
- ISBN-10: 3031013328
- Artikelnr.: 63575759
- Herstellerkennzeichnung
- Books on Demand GmbH
- In de Tarpen 42
- 22848 Norderstedt
- info@bod.de
- 040 53433511
- Lecture Notes in Computer Science 13205
- Verlag: Springer / Springer International Publishing / Springer, Berlin
- Artikelnr. des Verlages: 978-3-031-01332-4
- 1st ed. 2022
- Seitenzahl: 420
- Erscheinungstermin: 7. April 2022
- Englisch
- Abmessung: 235mm x 155mm x 23mm
- Gewicht: 633g
- ISBN-13: 9783031013324
- ISBN-10: 3031013328
- Artikelnr.: 63575759
- Herstellerkennzeichnung
- Books on Demand GmbH
- In de Tarpen 42
- 22848 Norderstedt
- info@bod.de
- 040 53433511
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.
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.