Advances in Intelligent Data Analysis XIX
19th International Symposium on Intelligent Data Analysis, IDA 2021, Porto, Portugal, April 26-28, 2021, Proceedings
Herausgegeben:Abreu, Pedro Henriques; Rodrigues, Pedro Pereira; Fernández, Alberto; Gama, João
Advances in Intelligent Data Analysis XIX
19th International Symposium on Intelligent Data Analysis, IDA 2021, Porto, Portugal, April 26-28, 2021, Proceedings
Herausgegeben:Abreu, Pedro Henriques; Rodrigues, Pedro Pereira; Fernández, Alberto; Gama, João
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This book constitutes the proceedings of the 19th International Symposium on Intelligent Data Analysis, IDA 2021, which was planned to take place in Porto, Portugal. Due to the COVID-19 pandemic the conference was held online during April 26-28, 2021. The 35 papers included in this book were carefully reviewed and selected from 113 submissions. The papers were organized in topical sections named: modeling with neural networks; modeling with statistical learning; modeling language and graphs; and modeling special data formats.
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This book constitutes the proceedings of the 19th International Symposium on Intelligent Data Analysis, IDA 2021, which was planned to take place in Porto, Portugal. Due to the COVID-19 pandemic the conference was held online during April 26-28, 2021.
The 35 papers included in this book were carefully reviewed and selected from 113 submissions. The papers were organized in topical sections named: modeling with neural networks; modeling with statistical learning; modeling language and graphs; and modeling special data formats.
The 35 papers included in this book were carefully reviewed and selected from 113 submissions. The papers were organized in topical sections named: modeling with neural networks; modeling with statistical learning; modeling language and graphs; and modeling special data formats.
Produktdetails
- Produktdetails
- Lecture Notes in Computer Science 12695
- Verlag: Springer / Springer International Publishing / Springer, Berlin
- Artikelnr. des Verlages: 978-3-030-74250-8
- 1st ed. 2021
- Seitenzahl: 472
- Erscheinungstermin: 13. April 2021
- Englisch
- Abmessung: 235mm x 155mm x 26mm
- Gewicht: 709g
- ISBN-13: 9783030742508
- ISBN-10: 3030742504
- Artikelnr.: 61378694
- Herstellerkennzeichnung Die Herstellerinformationen sind derzeit nicht verfügbar.
- Lecture Notes in Computer Science 12695
- Verlag: Springer / Springer International Publishing / Springer, Berlin
- Artikelnr. des Verlages: 978-3-030-74250-8
- 1st ed. 2021
- Seitenzahl: 472
- Erscheinungstermin: 13. April 2021
- Englisch
- Abmessung: 235mm x 155mm x 26mm
- Gewicht: 709g
- ISBN-13: 9783030742508
- ISBN-10: 3030742504
- Artikelnr.: 61378694
- Herstellerkennzeichnung Die Herstellerinformationen sind derzeit nicht verfügbar.
Modeling with Neural Networks.- Hyperspherical Weight Uncertainty in Neural Networks.- Partially Monotonic Learning for Neural Networks.- Multiple-Manifold Generation with an Ensemble GAN and Learned Noise Prior.- Simple, Efficient and Convenient Decentralized Multi-Task Learning for Neural Networks.- Deep Hybrid Neural Networks with Improved Weighted Word Embeddings for Sentiment Analysis.- Explaining Neural Networks by Decoding Layer Activations.- Analogical Embedding for Analogy-based Learning to Rank.- HORUS-NER: A Multimodal Named Entity Recognition Framework for Noisy Data.- Modeling with Statistical Learning.- Incremental Search Space Construction for Machine Learning Pipeline Synthesis.- Adversarial Vulnerability of Active Transfer Learning.- Revisiting Non-Specific Syndromic Surveillance.- Gradient Ascent for Best Response Regression.- Intelligent Structural Damage Detection: a Federated Learning Approach.- Composite surrogate for likelihood-freeBayesian optimisation in high-dimensional settings of activity-based transportation models.- Active Selection of Classification Features.- Feature Selection for Hierarchical Multi-Label Classification.- Bandit Algorithm for Both Unknown Best Position and Best Item Display on Web Pages.- Performance prediction for hardware-software configurations: A case study for video games.- avatar Automated Feature Wrangling for Machine Learning.- Modeling Language and Graphs.- Semantically Enriching Embeddings of Highly In ectable Verbs for Improving Intent Detection in a Romanian Home Assistant Scenario.- BoneBert: A BERT-based Automated Information Extraction System of Radiology Reports for Bone Fracture Detection and Diagnosis.- Linking the Dynamics of User Stance to the Structure of Online Discussions.- Unsupervised Methods for the Study of Transformer Embeddings.- A Framework for Authorial Clustering of Shorter Texts in Latent Semantic Spaces.- DeepGG: a Deep Graph Generator.- SINr: fast computing of Sparse Interpretable Node Representations is not a sin.- Detection of contextual anomalies in attributed graphs.- Ising-Based Louvain Method: Clustering Large Graphs with Specialized Hardware.- Modeling Special Data Formats.- Reducing Negative Impact of Noise in Boolean Matrix Factorization with Association Rules.- Z-Hist: A Temporal Abstraction of Multivariate Histogram Snapshots.- muppets: Multipurpose Table Segmentation.- SpLyCI: Integrating Spreadsheets by Recognising and Solving Layout Constraints.- RTL: A Robust Time Series Labeling Algorithm.- The Compromise of Data Privacy in Predictive Performance.- Efficient Privacy Preserving Distributed K-Means for Non-IID Data.
Modeling with Neural Networks.- Hyperspherical Weight Uncertainty in Neural Networks.- Partially Monotonic Learning for Neural Networks.- Multiple-Manifold Generation with an Ensemble GAN and Learned Noise Prior.- Simple, Efficient and Convenient Decentralized Multi-Task Learning for Neural Networks.- Deep Hybrid Neural Networks with Improved Weighted Word Embeddings for Sentiment Analysis.- Explaining Neural Networks by Decoding Layer Activations.- Analogical Embedding for Analogy-based Learning to Rank.- HORUS-NER: A Multimodal Named Entity Recognition Framework for Noisy Data.- Modeling with Statistical Learning.- Incremental Search Space Construction for Machine Learning Pipeline Synthesis.- Adversarial Vulnerability of Active Transfer Learning.- Revisiting Non-Specific Syndromic Surveillance.- Gradient Ascent for Best Response Regression.- Intelligent Structural Damage Detection: a Federated Learning Approach.- Composite surrogate for likelihood-freeBayesian optimisation in high-dimensional settings of activity-based transportation models.- Active Selection of Classification Features.- Feature Selection for Hierarchical Multi-Label Classification.- Bandit Algorithm for Both Unknown Best Position and Best Item Display on Web Pages.- Performance prediction for hardware-software configurations: A case study for video games.- avatar Automated Feature Wrangling for Machine Learning.- Modeling Language and Graphs.- Semantically Enriching Embeddings of Highly In ectable Verbs for Improving Intent Detection in a Romanian Home Assistant Scenario.- BoneBert: A BERT-based Automated Information Extraction System of Radiology Reports for Bone Fracture Detection and Diagnosis.- Linking the Dynamics of User Stance to the Structure of Online Discussions.- Unsupervised Methods for the Study of Transformer Embeddings.- A Framework for Authorial Clustering of Shorter Texts in Latent Semantic Spaces.- DeepGG: a Deep Graph Generator.- SINr: fast computing of Sparse Interpretable Node Representations is not a sin.- Detection of contextual anomalies in attributed graphs.- Ising-Based Louvain Method: Clustering Large Graphs with Specialized Hardware.- Modeling Special Data Formats.- Reducing Negative Impact of Noise in Boolean Matrix Factorization with Association Rules.- Z-Hist: A Temporal Abstraction of Multivariate Histogram Snapshots.- muppets: Multipurpose Table Segmentation.- SpLyCI: Integrating Spreadsheets by Recognising and Solving Layout Constraints.- RTL: A Robust Time Series Labeling Algorithm.- The Compromise of Data Privacy in Predictive Performance.- Efficient Privacy Preserving Distributed K-Means for Non-IID Data.