Advances in Intelligent Data Analysis XVIII: 18th International Symposium on Intelligent Data Analysis, IDA 2020, Konstanz, Germany, April 27–29, 2020, Proceedings

Author:   Michael R. Berthold ,  Ad Feelders ,  Georg Krempl
Publisher:   Springer Nature Switzerland AG
Edition:   2020 ed.
Volume:   12080
ISBN:  

9783030445836


Pages:   588
Publication Date:   02 April 2020
Format:   Paperback
Availability:   Manufactured on demand   Availability explained
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Advances in Intelligent Data Analysis XVIII: 18th International Symposium on Intelligent Data Analysis, IDA 2020, Konstanz, Germany, April 27–29, 2020, Proceedings


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Author:   Michael R. Berthold ,  Ad Feelders ,  Georg Krempl
Publisher:   Springer Nature Switzerland AG
Imprint:   Springer Nature Switzerland AG
Edition:   2020 ed.
Volume:   12080
Weight:   0.914kg
ISBN:  

9783030445836


ISBN 10:   3030445836
Pages:   588
Publication Date:   02 April 2020
Audience:   Professional and scholarly ,  Professional & Vocational
Format:   Paperback
Publisher's Status:   Active
Availability:   Manufactured on demand   Availability explained
We will order this item for you from a manufactured on demand supplier.

Table of Contents

Multivariate Time Series as Images: Imputation Using Convolutional Denoising Autoencoder.- Dual Sequential Variational Autoencoders for Fraud Detection.- A Principled Approach to Analyze Expressiveness and Accuracy of Graph Neural Networks.- Efficient Batch-Incremental Classification Using UMAP for Evolving Data Streams.- GraphMDL: Graph Pattern Selection Based on Minimum Description Length.- Towards Content Sensitivity Analysis.- Gibbs Sampling Subjectively Interesting Tiles.- Even Faster Exact k-Means Clustering.- Ising-Based Consensus Clustering on Special Purpose Hardware.- Transfer Learning by Learning Projections from Target to Source.- Computing Vertex-Vertex Dissimilarities Using Random Trees: Application to Clustering in Graphs.- Towards Evaluation of CNN Performance in Semantically Meaningful Latent Spaces.- Vouw: Geometric Pattern Mining Using the MDL Principle.- A Consensus Approach to Improve NMF Document Clustering.- Discriminative Bias for Learning Probabilistic Sentential Decision Diagrams.- Widening for MDL-Based Retail Signature Discovery.- Addressing the Resolution Limit and the Field of View Limit in Community Mining.- Estimating Uncertainty in Deep Learning for Reporting Confidence: An Application on Cell Type Prediction in Testes Based on Proteomics.- Adversarial Attacks Hidden in Plain Sight.- Enriched Weisfeiler-Lehman Kernel for Improved Graph Clustering of Source Code.- Overlapping Hierarchical Clustering (OHC).- Digital Footprints of International Migration on Twitter.- Percolation-Based Detection of Anomalous Subgraphs in Complex Networks.- A Late-Fusion Approach to Community Detection in Attributed Networks.- Reconciling Predictions in the Regression Setting: an Application to Bus Travel Time Prediction.- A Distribution Dependent and Independent Complexity Analysis of Manifold Regularization.- Actionable Subgroup Discovery and Urban Farm Optimization.- AVATAR - Machine Learning Pipeline Evaluation Using Surrogate Model.- Detection ofDerivative Discontinuities in Observational Data.- Improving Prediction with Causal Probabilistic Variables.- DO-U-Net for Segmentation and Counting.- Enhanced Word Embeddings for Anorexia Nervosa Detection on Social Media.- Event Recognition Based on Classification of Generated Image Captions.- Human-to-AI Coach: Improving Human Inputs to AI Systems.- Aleatoric and Epistemic Uncertainty with Random Forests.- Master your Metrics with Calibration.- Supervised Phrase-Boundary Embeddings.- Predicting Remaining Useful Life with Similarity-Based Priors.- Orometric Methods in Bounded Metric Data.- Interpretable Neuron Structuring with Graph Spectral Regularization.- Comparing the Preservation of Network Properties by Graph Embeddings.- Making Learners (More) Monotone.- Combining Machine Learning and Simulation to a Hybrid Modelling Approach.- LiBRe: Label-Wise Selection of Base Learners in Binary Relevance for Multi-Label Classification.- Angle-Based Crowding Degree Estimation for Many-Objective Optimization.

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