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Advances in Intelligent Data Analysis XIX : 19th International Symposium on Intelligent Data Analysis, IDA 2021, Porto, Portugal, April 26-28, 2021, Proceedings / edited by Pedro Henriques Abreu, Pedro Pereira Rodrigues, Alberto Fernández, João Gama.
- Format:
- Book
- Series:
- Computer Science (SpringerNature-11645)
- LNCS sublibrary. Information systems and applications, incl. Internet/Web, and HCI ; SL 3, 12695
- Information Systems and Applications, incl. Internet/Web, and HCI ; 12695
- Language:
- English
- Subjects (All):
- Database management.
- Social sciences-Data processing.
- Algorithms.
- Education-Data processing.
- Natural language processing (Computer science).
- Database Management.
- Computer Application in Social and Behavioral Sciences.
- Design and Analysis of Algorithms.
- Computers and Education.
- Natural Language Processing (NLP).
- Local Subjects:
- Database Management.
- Computer Application in Social and Behavioral Sciences.
- Design and Analysis of Algorithms.
- Computers and Education.
- Natural Language Processing (NLP).
- Physical Description:
- 1 online resource (XVI, 454 pages) : 138 illustrations, 107 illustrations in color.
- Edition:
- 1st ed. 2021.
- Contained In:
- Springer Nature eBook
- Place of Publication:
- Cham : Springer International Publishing : Imprint: Springer, 2021.
- System Details:
- text file PDF
- Summary:
- 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.
- Contents:
- 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-free Bayesian 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.
- Other Format:
- Printed edition:
- ISBN:
- 978-3-030-74251-5
- 9783030742515
- Access Restriction:
- Restricted for use by site license.
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