Advances in Intelligent Data Analysis XVIII [[electronic resource] ] : 18th International Symposium on Intelligent Data Analysis, IDA 2020, Konstanz, Germany, April 27–29, 2020, Proceedings / / edited by Michael R. Berthold, Ad Feelders, Georg Krempl
| Advances in Intelligent Data Analysis XVIII [[electronic resource] ] : 18th International Symposium on Intelligent Data Analysis, IDA 2020, Konstanz, Germany, April 27–29, 2020, Proceedings / / edited by Michael R. Berthold, Ad Feelders, Georg Krempl |
| Autore | Berthold Michael |
| Edizione | [1st ed. 2020.] |
| Pubbl/distr/stampa | Cham, : Springer Nature, 2020 |
| Descrizione fisica | 1 online resource (XIV, 588 p. 210 illus., 132 illus. in color.) |
| Disciplina | 005.74 |
| Collana | Information Systems and Applications, incl. Internet/Web, and HCI |
| Soggetto topico |
Database management
Data mining Computers Machine learning Computer organization Database Management Data Mining and Knowledge Discovery Computing Milieux Machine Learning Computer Systems Organization and Communication Networks |
| Soggetto non controllato |
Database Management
Data Mining and Knowledge Discovery Computing Milieux Machine Learning Computer Systems Organization and Communication Networks open access data mining learning systems classification clustering semantics learning algorithms supervised learning association rules social networks graphic methods neural networks artificial intelligence computer vision correlation analysis databases education engineering graph theory image analysis Databases Database programming Data mining Expert systems / knowledge-based systems Information technology: general issues Machine learning Computer networking & communications |
| ISBN | 3-030-44584-4 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | 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 of Derivative 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. |
| Record Nr. | UNISA-996418219903316 |
Berthold Michael
|
||
| Cham, : Springer Nature, 2020 | ||
| Lo trovi qui: Univ. di Salerno | ||
| ||
Advances in Intelligent Data Analysis XVIII : 18th International Symposium on Intelligent Data Analysis, IDA 2020, Konstanz, Germany, April 27–29, 2020, Proceedings / / edited by Michael R. Berthold, Ad Feelders, Georg Krempl
| Advances in Intelligent Data Analysis XVIII : 18th International Symposium on Intelligent Data Analysis, IDA 2020, Konstanz, Germany, April 27–29, 2020, Proceedings / / edited by Michael R. Berthold, Ad Feelders, Georg Krempl |
| Autore | Berthold Michael |
| Edizione | [1st ed. 2020.] |
| Pubbl/distr/stampa | Cham, : Springer Nature, 2020 |
| Descrizione fisica | 1 online resource (XIV, 588 p. 210 illus., 132 illus. in color.) |
| Disciplina | 005.74 |
| Collana | Information Systems and Applications, incl. Internet/Web, and HCI |
| Soggetto topico |
Database management
Data mining Computers Machine learning Computer engineering Computer networks Database Management Data Mining and Knowledge Discovery Computing Milieux Machine Learning Computer Engineering and Networks |
| ISBN |
9783030445843
3030445844 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | 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. |
| Record Nr. | UNINA-9910404119303321 |
Berthold Michael
|
||
| Cham, : Springer Nature, 2020 | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Advances in Intelligent Data Analysis XXIII : 23rd International Symposium on Intelligent Data Analysis, IDA 2025, Konstanz, Germany, May 7–9, 2025, Proceedings / / edited by Georg Krempl, Kai Puolamäki, Ioanna Miliou
| Advances in Intelligent Data Analysis XXIII : 23rd International Symposium on Intelligent Data Analysis, IDA 2025, Konstanz, Germany, May 7–9, 2025, Proceedings / / edited by Georg Krempl, Kai Puolamäki, Ioanna Miliou |
| Edizione | [1st ed. 2025.] |
| Pubbl/distr/stampa | Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2025 |
| Descrizione fisica | 1 online resource (XVI, 486 p. 117 illus., 111 illus. in color.) |
| Disciplina | 005.7 |
| Collana | Lecture Notes in Computer Science |
| Soggetto topico |
Database management
Education - Data processing Image processing - Digital techniques Computer vision Artificial intelligence Machine learning Natural language processing (Computer science) Database Management System Computers and Education Computer Imaging, Vision, Pattern Recognition and Graphics Artificial Intelligence Machine Learning Natural Language Processing (NLP) |
| ISBN | 3-031-91398-1 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Applications of Data Science -- Credal Knowledge Tracing for Imprecise and Uncertain MCQ -- Development of Models to Quantify Training Load in Outdoor Running using Inertial Sensors -- Estimating the Learning Capacity of Bacterial Metabolic Networks -- Semi-supervised learning with pairwise instance comparisons for medical instance classification -- Local-global Data Augmentation for Contrastive Learning in Static Sign Language Recognition -- SiamCircle: Trajectory Representation Learning in Free Settings -- Synthetic Tabular Data Detection In the Wild -- Assessing the Impact of Graph Structure Learning in Graph Deviation Networks -- Foundations of Data Science -- The When and How of Target Variable Transformations -- Balancing performance and scalability of demand forecasting ML models -- Balancing global importance and source proximity for personalized recommendations using random walk length -- Counterintuitive Behavior of Clustering Quality: Findings for K-Means on Synthetic and Real Data -- BOWSA: a contribution of sensitivity analysis to improve Bayesian optimization for parameter tuning -- Overfitting in Combined Algorithm Selection and Hyperparameter Optimization -- Local Subgroup Discovery on Attributed Network Graphs -- Imposing Constraints in Probabilistic Circuits via Gradient Optimization -- Natural Language Processing -- Improving Next Tokens via Second-Last Predictions with ’Generate and Refine’ -- Detection of Large Language Model Contamination with Tabular Data -- Imbalanced Data Clustering via Targeted Data Augmentation Using GMM and LLM -- Make Literature-Based Discovery Great Again through Reproducible Pipelines -- Extracting information in a low-resource setting: case study on bioinformatics workflows -- Vocabulary Quality in NLP Datasets: An Autoencoder-Based Framework Across Domains and Languages -- Temporal and Streaming Data Expertise Prediction of Tetris Players Using Eye Tracking Information -- Integrating Inverse and Forward Modeling for Sparse Temporal Data from Sensor Networks -- Bridging Spatial and Temporal Contexts: Sparse Transfer Learning -- Meta-learning and Data Augmentation for Stress Testing Forecasting Models -- Pragmatic Paradigm for Multi-stream Regression -- Two-in-one Models for Event Prediction and Time Series Forecasting. Comparison of Four Deep Learning Approaches to Simulate a Digital Patient under Anesthesia -- An Analysis of Temporal Dropout in Earth Observation Time Series for Regression Tasks -- Performative Drift Resistant Classification using Generative Domain Adversarial Networks -- Explainable and Interpretable Data Science -- Extracting Moore Machines from Transformers using Queries and Counterexamples -- Obtaining Example-Based Explanations from Deep Neural Networks -- Relevance-aware Algorithmic Recourse -- Expanding Polynomial Kernels for Global and Local Explanations of Support Vector Machines -- A Constrained Declarative Based Approach for Explainable Clustering. |
| Record Nr. | UNINA-9911001468703321 |
| Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2025 | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Advances in Intelligent Data Analysis XXIII : 23rd International Symposium on Intelligent Data Analysis, IDA 2025, Konstanz, Germany, May 7–9, 2025, Proceedings / / edited by Georg Krempl, Kai Puolamäki, Ioanna Miliou
| Advances in Intelligent Data Analysis XXIII : 23rd International Symposium on Intelligent Data Analysis, IDA 2025, Konstanz, Germany, May 7–9, 2025, Proceedings / / edited by Georg Krempl, Kai Puolamäki, Ioanna Miliou |
| Edizione | [1st ed. 2025.] |
| Pubbl/distr/stampa | Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2025 |
| Descrizione fisica | 1 online resource (XVI, 486 p. 117 illus., 111 illus. in color.) |
| Disciplina | 005.7 |
| Collana | Lecture Notes in Computer Science |
| Soggetto topico |
Database management
Education - Data processing Image processing - Digital techniques Computer vision Artificial intelligence Machine learning Natural language processing (Computer science) Database Management System Computers and Education Computer Imaging, Vision, Pattern Recognition and Graphics Artificial Intelligence Machine Learning Natural Language Processing (NLP) |
| ISBN | 3-031-91398-1 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Applications of Data Science -- Credal Knowledge Tracing for Imprecise and Uncertain MCQ -- Development of Models to Quantify Training Load in Outdoor Running using Inertial Sensors -- Estimating the Learning Capacity of Bacterial Metabolic Networks -- Semi-supervised learning with pairwise instance comparisons for medical instance classification -- Local-global Data Augmentation for Contrastive Learning in Static Sign Language Recognition -- SiamCircle: Trajectory Representation Learning in Free Settings -- Synthetic Tabular Data Detection In the Wild -- Assessing the Impact of Graph Structure Learning in Graph Deviation Networks -- Foundations of Data Science -- The When and How of Target Variable Transformations -- Balancing performance and scalability of demand forecasting ML models -- Balancing global importance and source proximity for personalized recommendations using random walk length -- Counterintuitive Behavior of Clustering Quality: Findings for K-Means on Synthetic and Real Data -- BOWSA: a contribution of sensitivity analysis to improve Bayesian optimization for parameter tuning -- Overfitting in Combined Algorithm Selection and Hyperparameter Optimization -- Local Subgroup Discovery on Attributed Network Graphs -- Imposing Constraints in Probabilistic Circuits via Gradient Optimization -- Natural Language Processing -- Improving Next Tokens via Second-Last Predictions with ’Generate and Refine’ -- Detection of Large Language Model Contamination with Tabular Data -- Imbalanced Data Clustering via Targeted Data Augmentation Using GMM and LLM -- Make Literature-Based Discovery Great Again through Reproducible Pipelines -- Extracting information in a low-resource setting: case study on bioinformatics workflows -- Vocabulary Quality in NLP Datasets: An Autoencoder-Based Framework Across Domains and Languages -- Temporal and Streaming Data Expertise Prediction of Tetris Players Using Eye Tracking Information -- Integrating Inverse and Forward Modeling for Sparse Temporal Data from Sensor Networks -- Bridging Spatial and Temporal Contexts: Sparse Transfer Learning -- Meta-learning and Data Augmentation for Stress Testing Forecasting Models -- Pragmatic Paradigm for Multi-stream Regression -- Two-in-one Models for Event Prediction and Time Series Forecasting. Comparison of Four Deep Learning Approaches to Simulate a Digital Patient under Anesthesia -- An Analysis of Temporal Dropout in Earth Observation Time Series for Regression Tasks -- Performative Drift Resistant Classification using Generative Domain Adversarial Networks -- Explainable and Interpretable Data Science -- Extracting Moore Machines from Transformers using Queries and Counterexamples -- Obtaining Example-Based Explanations from Deep Neural Networks -- Relevance-aware Algorithmic Recourse -- Expanding Polynomial Kernels for Global and Local Explanations of Support Vector Machines -- A Constrained Declarative Based Approach for Explainable Clustering. |
| Record Nr. | UNISA-996660361603316 |
| Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2025 | ||
| Lo trovi qui: Univ. di Salerno | ||
| ||