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Advances in Intelligent Data Analysis V [[electronic resource] ] : 5th International Symposium on Intelligent Data Analysis, IDA 2003, Berlin, Germany, August 28-30, 2003, Proceedings / / edited by Michael R. Berthold, Hans-Joachim Lenz, Elizabeth Bradley, Rudolf Kruse, Christian Borgelt
| Advances in Intelligent Data Analysis V [[electronic resource] ] : 5th International Symposium on Intelligent Data Analysis, IDA 2003, Berlin, Germany, August 28-30, 2003, Proceedings / / edited by Michael R. Berthold, Hans-Joachim Lenz, Elizabeth Bradley, Rudolf Kruse, Christian Borgelt |
| Edizione | [1st ed. 2003.] |
| Pubbl/distr/stampa | Berlin, Heidelberg : , : Springer Berlin Heidelberg : , : Imprint : Springer, , 2003 |
| Descrizione fisica | 1 online resource (XVI, 632 p.) |
| Disciplina | 519.5 |
| Collana | Lecture Notes in Computer Science |
| Soggetto topico |
Artificial intelligence
Information storage and retrieval Mathematical statistics Pattern recognition Application software Information technology Business—Data processing Artificial Intelligence Information Storage and Retrieval Probability and Statistics in Computer Science Pattern Recognition Computer Appl. in Administrative Data Processing IT in Business |
| ISBN | 3-540-45231-1 |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Machine Learning -- Pruning for Monotone Classification Trees -- Regularized Learning with Flexible Constraints -- Learning to Answer Emails -- A Semi-supervised Method for Learning the Structure of Robot Environment Interactions -- Using Domain Specific Knowledge for Automated Modeling -- Resolving Rule Conflicts with Double Induction -- A Novel Partial-Memory Learning Algorithm Based on Grey Relational Structure -- Constructing Hierarchical Rule Systems -- Text Categorization Using Hybrid Multiple Model Schemes -- Probability and Topology -- Learning Dynamic Bayesian Networks from Multivariate Time Series with Changing Dependencies -- Topology and Intelligent Data Analysis -- Coherent Conditional Probability as a Measure of Information of the Relevant Conditioning Events -- Very Predictive Ngrams for Space-Limited Probabilistic Models -- Interval Estimation Naïve Bayes -- Mining Networks and Central Entities in Digital Libraries. A Graph Theoretic Approach Applied to Co-author Networks -- Classification and Pattern Recognition -- Learning Linear Classifiers Sensitive to Example Dependent and Noisy Costs -- An Effective Associative Memory for Pattern Recognition -- Similarity Based Classification -- Numerical Attributes in Decision Trees: A Hierarchical Approach -- Similarity-Based Neural Networks for Applications in Computational Molecular Biology -- Combining Pairwise Classifiers with Stacking -- APRIORI-SD: Adapting Association Rule Learning to Subgroup Discovery -- Solving Classification Problems Using Infix Form Genetic Programming -- Clustering -- What Is Fuzzy about Fuzzy Clustering? Understanding and Improving the Concept of the Fuzzifier -- A Mixture Model Approach for Binned Data Clustering -- Fuzzy Clustering Based Segmentation of Time-Series -- An Iterated Local Search Approach for Minimum Sum-of-Squares Clustering -- Data Clustering in Tolerance Space -- Refined Shared Nearest Neighbors Graph for Combining Multiple Data Clusterings -- Clustering Mobile Trajectories for Resource Allocation in Mobile Environments -- Fuzzy Clustering of Short Time-Series and Unevenly Distributed Sampling Points -- Combining and Comparing Cluster Methods in a Receptor Database -- Applications -- Selective Sampling with a Hierarchical Latent Variable Model -- Obtaining Quality Microarray Data via Image Reconstruction -- Large Scale Mining of Molecular Fragments with Wildcards -- Genome-Wide Prokaryotic Promoter Recognition Based on Sequence Alignment Kernel -- Towards Automated Electrocardiac Map Interpretation: An Intelligent Contouring Tool Based on Spatial Aggregation -- Study of Canada/US Dollar Exchange Rate Movements Using Recurrent Neural Network Model of FX-Market -- Gaussian Mixture Density Estimation Applied to Microarray Data -- Classification of Protein Localisation Patterns via Supervised Neural Network Learning -- Applying Intelligent Data Analysis to Coupling Relationships in Object-Oriented Software -- The Smaller the Better: Comparison of Two Approaches for Sales Rate Prediction -- Modeling -- A Multiagent-Based Constructive Approach for Feedforward Neural Networks -- Evolutionary System Identification via Descriptive Takagi Sugeno Fuzzy Systems -- Minimum Message Length Criterion for Second-Order Polynomial Model Selection Applied to Tropical Cyclone Intensity Forecasting -- On the Use of the GTM Algorithm for Mode Detection -- Regularization Methods for Additive Models -- Automated Detection of Influenza Epidemics with Hidden Markov Models -- Guided Incremental Construction of Belief Networks -- Distributed Regression for Heterogeneous Data Sets -- (Data) Preprocessing -- A Logical Formalisation of the Fellegi-Holt Method of Data Cleaning -- Compression Technique Preserving Correlations of a Multivariate Temporal Sequence -- Condensed Representations in Presence of Missing Values -- Measures of Rule Quality for Feature Selection in Text Categorization -- Genetic Approach to Constructive Induction Based on Non-algebraic Feature Representation -- Active Feature Selection Based on a Very Limited Number of Entities. |
| Record Nr. | UNINA-9910767545103321 |
| Berlin, Heidelberg : , : Springer Berlin Heidelberg : , : Imprint : Springer, , 2003 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Advances in Intelligent Data Analysis VI [[electronic resource] ] : 6th International Symposium on Intelligent Data Analysis, IDA 2005, Madrid, Spain, September 8-10, 2005, Proceedings / / edited by A. Fazel Famili, Joost N. Kok, José M. Pena, Arno Siebes, Ad Feelders
| Advances in Intelligent Data Analysis VI [[electronic resource] ] : 6th International Symposium on Intelligent Data Analysis, IDA 2005, Madrid, Spain, September 8-10, 2005, Proceedings / / edited by A. Fazel Famili, Joost N. Kok, José M. Pena, Arno Siebes, Ad Feelders |
| Edizione | [1st ed. 2005.] |
| Pubbl/distr/stampa | Berlin, Heidelberg : , : Springer Berlin Heidelberg : , : Imprint : Springer, , 2005 |
| Descrizione fisica | 1 online resource (XIV, 534 p.) |
| Disciplina | 006.3/3 |
| Collana | Information Systems and Applications, incl. Internet/Web, and HCI |
| Soggetto topico |
Artificial intelligence
Information storage and retrieval Mathematical statistics Pattern recognition Information technology Business—Data processing Artificial Intelligence Information Storage and Retrieval Probability and Statistics in Computer Science Pattern Recognition IT in Business |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Probabilistic Latent Clustering of Device Usage -- Condensed Nearest Neighbor Data Domain Description -- Balancing Strategies and Class Overlapping -- Modeling Conditional Distributions of Continuous Variables in Bayesian Networks -- Kernel K-Means for Categorical Data -- Using Genetic Algorithms to Improve Accuracy of Economical Indexes Prediction -- A Distance-Based Method for Preference Information Retrieval in Paired Comparisons -- Knowledge Discovery in the Identification of Differentially Expressed Genes in Tumoricidal Macrophage -- Searching for Meaningful Feature Interactions with Backward-Chaining Rule Induction -- Exploring Hierarchical Rule Systems in Parallel Coordinates -- Bayesian Networks Learning for Gene Expression Datasets -- Pulse: Mining Customer Opinions from Free Text -- Keystroke Analysis of Different Languages: A Case Study -- Combining Bayesian Networks with Higher-Order Data Representations -- Removing Statistical Biases in Unsupervised Sequence Learning -- Learning from Ambiguously Labeled Examples -- Learning Label Preferences: Ranking Error Versus Position Error -- FCLib: A Library for Building Data Analysis and Data Discovery Tools -- A Knowledge-Based Model for Analyzing GSM Network Performance -- Sentiment Classification Using Information Extraction Technique -- Extending the SOM Algorithm to Visualize Word Relationships -- Towards Automatic and Optimal Filtering Levels for Feature Selection in Text Categorization -- Block Clustering of Contingency Table and Mixture Model -- Adaptive Classifier Combination for Visual Information Processing Using Data Context-Awareness -- Self-poised Ensemble Learning -- Discriminative Remote Homology Detection Using Maximal Unique Sequence Matches -- From Local Pattern Mining to Relevant Bi-cluster Characterization -- Machine-Learning with Cellular Automata -- MDS polar : A New Approach for Dimension Reduction to Visualize High Dimensional Data -- Miner Ants Colony: A New Approach to Solve a Mine Planning Problem -- Extending the GA-EDA Hybrid Algorithm to Study Diversification and Intensification in GAs and EDAs -- Spatial Approach to Pose Variations in Face Verification -- Analysis of Feature Rankings for Classification -- A Mixture Model-Based On-line CEM Algorithm -- Reliable Hierarchical Clustering with the Self-organizing Map -- Statistical Recognition of Noun Phrases in Unrestricted Text -- Successive Restrictions Algorithm in Bayesian Networks -- Modelling the Relationship Between Streamflow and Electrical Conductivity in Hollin Creek, Southeastern Australia -- Biological Cluster Validity Indices Based on the Gene Ontology -- An Evaluation of Filter and Wrapper Methods for Feature Selection in Categorical Clustering -- Dealing with Data Corruption in Remote Sensing -- Regularized Least-Squares for Parse Ranking -- Bayesian Network Classifiers for Time-Series Microarray Data -- Feature Discovery in Classification Problems -- A New Hybrid NM Method and Particle Swarm Algorithm for Multimodal Function Optimization -- Detecting Groups of Anomalously Similar Objects in Large Data Sets. |
| Record Nr. | UNISA-996465436103316 |
| Berlin, Heidelberg : , : Springer Berlin Heidelberg : , : Imprint : Springer, , 2005 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. di Salerno | ||
| ||
Advances in Intelligent Data Analysis VI [[electronic resource] ] : 6th International Symposium on Intelligent Data Analysis, IDA 2005, Madrid, Spain, September 8-10, 2005, Proceedings / / edited by A. Fazel Famili, Joost N. Kok, José M. Pena, Arno Siebes, Ad Feelders
| Advances in Intelligent Data Analysis VI [[electronic resource] ] : 6th International Symposium on Intelligent Data Analysis, IDA 2005, Madrid, Spain, September 8-10, 2005, Proceedings / / edited by A. Fazel Famili, Joost N. Kok, José M. Pena, Arno Siebes, Ad Feelders |
| Edizione | [1st ed. 2005.] |
| Pubbl/distr/stampa | Berlin, Heidelberg : , : Springer Berlin Heidelberg : , : Imprint : Springer, , 2005 |
| Descrizione fisica | 1 online resource (XIV, 534 p.) |
| Disciplina | 006.3/3 |
| Collana | Information Systems and Applications, incl. Internet/Web, and HCI |
| Soggetto topico |
Artificial intelligence
Information storage and retrieval Mathematical statistics Pattern recognition Information technology Business—Data processing Artificial Intelligence Information Storage and Retrieval Probability and Statistics in Computer Science Pattern Recognition IT in Business |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Probabilistic Latent Clustering of Device Usage -- Condensed Nearest Neighbor Data Domain Description -- Balancing Strategies and Class Overlapping -- Modeling Conditional Distributions of Continuous Variables in Bayesian Networks -- Kernel K-Means for Categorical Data -- Using Genetic Algorithms to Improve Accuracy of Economical Indexes Prediction -- A Distance-Based Method for Preference Information Retrieval in Paired Comparisons -- Knowledge Discovery in the Identification of Differentially Expressed Genes in Tumoricidal Macrophage -- Searching for Meaningful Feature Interactions with Backward-Chaining Rule Induction -- Exploring Hierarchical Rule Systems in Parallel Coordinates -- Bayesian Networks Learning for Gene Expression Datasets -- Pulse: Mining Customer Opinions from Free Text -- Keystroke Analysis of Different Languages: A Case Study -- Combining Bayesian Networks with Higher-Order Data Representations -- Removing Statistical Biases in Unsupervised Sequence Learning -- Learning from Ambiguously Labeled Examples -- Learning Label Preferences: Ranking Error Versus Position Error -- FCLib: A Library for Building Data Analysis and Data Discovery Tools -- A Knowledge-Based Model for Analyzing GSM Network Performance -- Sentiment Classification Using Information Extraction Technique -- Extending the SOM Algorithm to Visualize Word Relationships -- Towards Automatic and Optimal Filtering Levels for Feature Selection in Text Categorization -- Block Clustering of Contingency Table and Mixture Model -- Adaptive Classifier Combination for Visual Information Processing Using Data Context-Awareness -- Self-poised Ensemble Learning -- Discriminative Remote Homology Detection Using Maximal Unique Sequence Matches -- From Local Pattern Mining to Relevant Bi-cluster Characterization -- Machine-Learning with Cellular Automata -- MDS polar : A New Approach for Dimension Reduction to Visualize High Dimensional Data -- Miner Ants Colony: A New Approach to Solve a Mine Planning Problem -- Extending the GA-EDA Hybrid Algorithm to Study Diversification and Intensification in GAs and EDAs -- Spatial Approach to Pose Variations in Face Verification -- Analysis of Feature Rankings for Classification -- A Mixture Model-Based On-line CEM Algorithm -- Reliable Hierarchical Clustering with the Self-organizing Map -- Statistical Recognition of Noun Phrases in Unrestricted Text -- Successive Restrictions Algorithm in Bayesian Networks -- Modelling the Relationship Between Streamflow and Electrical Conductivity in Hollin Creek, Southeastern Australia -- Biological Cluster Validity Indices Based on the Gene Ontology -- An Evaluation of Filter and Wrapper Methods for Feature Selection in Categorical Clustering -- Dealing with Data Corruption in Remote Sensing -- Regularized Least-Squares for Parse Ranking -- Bayesian Network Classifiers for Time-Series Microarray Data -- Feature Discovery in Classification Problems -- A New Hybrid NM Method and Particle Swarm Algorithm for Multimodal Function Optimization -- Detecting Groups of Anomalously Similar Objects in Large Data Sets. |
| Record Nr. | UNINA-9910483204003321 |
| Berlin, Heidelberg : , : Springer Berlin Heidelberg : , : Imprint : Springer, , 2005 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Advances in intelligent data analysis VII : 7th International Symposium on Intelligent Data Analysis, IDA 2007, Ljubljana, Slovenia, September 6-8, 2007, proceedings / / Michael R. Berthold, John Shawe-Taylor, Nada Lavrač (editors)
| Advances in intelligent data analysis VII : 7th International Symposium on Intelligent Data Analysis, IDA 2007, Ljubljana, Slovenia, September 6-8, 2007, proceedings / / Michael R. Berthold, John Shawe-Taylor, Nada Lavrač (editors) |
| Edizione | [1st ed. 2007.] |
| Pubbl/distr/stampa | Berlin ; ; Heidelberg : , : Springer, , [2007] |
| Descrizione fisica | 1 online resource (XIV, 382 p.) |
| Disciplina | 006.33 |
| Collana | Lecture notes in computer science |
| Soggetto topico |
Mathematical statistics
Mathematical statistics - Data processing Expert systems (Computer science) |
| ISBN | 3-540-74825-3 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Statistical Data Analysis -- Compact and Understandable Descriptions of Mixtures of Bernoulli Distributions -- Multiplicative Updates for L 1–Regularized Linear and Logistic Regression -- Learning to Align: A Statistical Approach -- Transductive Reliability Estimation for Kernel Based Classifiers -- Bayesian Approaches -- Parameter Learning for Bayesian Networks with Strict Qualitative Influences -- Tree Augmented Naive Bayes for Regression Using Mixtures of Truncated Exponentials: Application to Higher Education Management -- Clustering Methods -- DENCLUE 2.0: Fast Clustering Based on Kernel Density Estimation -- Visualising the Cluster Structure of Data Streams -- Relational Topographic Maps -- Ensemble Learning -- Incremental Learning with Multiple Classifier Systems Using Correction Filters for Classification -- Combining Bagging and Random Subspaces to Create Better Ensembles -- Two Bagging Algorithms with Coupled Learners to Encourage Diversity -- Ranking -- Relational Algebra for Ranked Tables with Similarities: Properties and Implementation -- A New Way to Aggregate Preferences: Application to Eurovision Song Contests -- Trees -- Conditional Classification Trees Using Instrumental Variables -- Robust Tree-Based Incremental Imputation Method for Data Fusion -- Sequence/ Time Series Analysis -- Making Time: Pseudo Time-Series for the Temporal Analysis of Cross Section Data -- Recurrent Predictive Models for Sequence Segmentation -- Sequence Classification Using Statistical Pattern Recognition -- Knowledge Discovery -- Subrule Analysis and the Frequency-Confidence Diagram -- A Partial Correlation-Based Algorithm for Causal Structure Discovery with Continuous Variables -- Visualization -- Visualizing Sets of Partial Rankings -- A Partially Supervised Metric Multidimensional Scaling Algorithm for Textual Data Visualization -- Landscape Multidimensional Scaling -- Text Mining -- A Support Vector Machine Approach to Dutch Part-of-Speech Tagging -- Towards Adaptive Web Mining: Histograms and Contexts in Text Data Clustering -- Does SVM Really Scale Up to Large Bag of Words Feature Spaces? -- Bioinformatics -- Noise Filtering and Microarray Image Reconstruction Via Chained Fouriers -- Motif Discovery Using Multi-Objective Genetic Algorithm in Biosequences -- Soft Topographic Map for Clustering and Classification of Bacteria -- Applications -- Fuzzy Logic Based Gait Classification for Hemiplegic Patients -- Traffic Sign Recognition Using Discriminative Local Features -- Novelty Detection in Patient Histories: Experiments with Measures Based on Text Compression. |
| Altri titoli varianti |
Advances in intelligent data analysis 7
Advances in intelligent data analysis seven |
| Record Nr. | UNINA-9910484403103321 |
| Berlin ; ; Heidelberg : , : Springer, , [2007] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Advances in intelligent data analysis VII : 7th International Symposium on Intelligent Data Analysis, IDA 2007, Ljubljana, Slovenia, September 6-8, 2007, proceedings / / Michael R. Berthold, John Shawe-Taylor, Nada Lavrač (editors)
| Advances in intelligent data analysis VII : 7th International Symposium on Intelligent Data Analysis, IDA 2007, Ljubljana, Slovenia, September 6-8, 2007, proceedings / / Michael R. Berthold, John Shawe-Taylor, Nada Lavrač (editors) |
| Edizione | [1st ed. 2007.] |
| Pubbl/distr/stampa | Berlin ; ; Heidelberg : , : Springer, , [2007] |
| Descrizione fisica | 1 online resource (XIV, 382 p.) |
| Disciplina | 006.33 |
| Collana | Lecture notes in computer science |
| Soggetto topico |
Mathematical statistics
Mathematical statistics - Data processing Expert systems (Computer science) |
| ISBN | 3-540-74825-3 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Statistical Data Analysis -- Compact and Understandable Descriptions of Mixtures of Bernoulli Distributions -- Multiplicative Updates for L 1–Regularized Linear and Logistic Regression -- Learning to Align: A Statistical Approach -- Transductive Reliability Estimation for Kernel Based Classifiers -- Bayesian Approaches -- Parameter Learning for Bayesian Networks with Strict Qualitative Influences -- Tree Augmented Naive Bayes for Regression Using Mixtures of Truncated Exponentials: Application to Higher Education Management -- Clustering Methods -- DENCLUE 2.0: Fast Clustering Based on Kernel Density Estimation -- Visualising the Cluster Structure of Data Streams -- Relational Topographic Maps -- Ensemble Learning -- Incremental Learning with Multiple Classifier Systems Using Correction Filters for Classification -- Combining Bagging and Random Subspaces to Create Better Ensembles -- Two Bagging Algorithms with Coupled Learners to Encourage Diversity -- Ranking -- Relational Algebra for Ranked Tables with Similarities: Properties and Implementation -- A New Way to Aggregate Preferences: Application to Eurovision Song Contests -- Trees -- Conditional Classification Trees Using Instrumental Variables -- Robust Tree-Based Incremental Imputation Method for Data Fusion -- Sequence/ Time Series Analysis -- Making Time: Pseudo Time-Series for the Temporal Analysis of Cross Section Data -- Recurrent Predictive Models for Sequence Segmentation -- Sequence Classification Using Statistical Pattern Recognition -- Knowledge Discovery -- Subrule Analysis and the Frequency-Confidence Diagram -- A Partial Correlation-Based Algorithm for Causal Structure Discovery with Continuous Variables -- Visualization -- Visualizing Sets of Partial Rankings -- A Partially Supervised Metric Multidimensional Scaling Algorithm for Textual Data Visualization -- Landscape Multidimensional Scaling -- Text Mining -- A Support Vector Machine Approach to Dutch Part-of-Speech Tagging -- Towards Adaptive Web Mining: Histograms and Contexts in Text Data Clustering -- Does SVM Really Scale Up to Large Bag of Words Feature Spaces? -- Bioinformatics -- Noise Filtering and Microarray Image Reconstruction Via Chained Fouriers -- Motif Discovery Using Multi-Objective Genetic Algorithm in Biosequences -- Soft Topographic Map for Clustering and Classification of Bacteria -- Applications -- Fuzzy Logic Based Gait Classification for Hemiplegic Patients -- Traffic Sign Recognition Using Discriminative Local Features -- Novelty Detection in Patient Histories: Experiments with Measures Based on Text Compression. |
| Altri titoli varianti |
Advances in intelligent data analysis 7
Advances in intelligent data analysis seven |
| Record Nr. | UNISA-996465748403316 |
| Berlin ; ; Heidelberg : , : Springer, , [2007] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. di Salerno | ||
| ||
Advances in intelligent data analysis XIX : 19th International Symposium on Intelligent Data Analysis, IDA 2021, Porto, Portugal, April 26-28, 2021 : proceedings / / Pedro Henriques Abreu [and three others], (editors)
| Advances in intelligent data analysis XIX : 19th International Symposium on Intelligent Data Analysis, IDA 2021, Porto, Portugal, April 26-28, 2021 : proceedings / / Pedro Henriques Abreu [and three others], (editors) |
| Pubbl/distr/stampa | Cham, Switzerland : , : Springer, , [2021] |
| Descrizione fisica | 1 online resource (xvi, 454 pages) |
| Disciplina | 006.4 |
| Collana | Lecture notes in computer science |
| Soggetto topico |
Pattern recognition systems
Mathematical statistics Mathematical statistics - Data processing |
| ISBN | 3-030-74251-2 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Intro -- Preface -- Organization -- Contents -- Modeling with Neural Networks -- Hyperspherical Weight Uncertainty in Neural Networks -- 1 Introduction -- 2 Background: On Gaussian Distributions -- 3 Hypersphere Bayesian Neural Networks -- 4 Results -- 4.1 Non-linear Regression -- 4.2 Image Classification -- 4.3 Measuring Uncertainty -- 4.4 Active Learning Using Uncertainty Quantification -- 4.5 Variational Auto-encoders -- 5 Conclusion -- References -- Partially Monotonic Learning for Neural Networks -- 1 Introduction -- 2 Related Work -- 3 Monotonicity -- 4 Partially Monotonic Learning -- 4.1 Loss Function -- 5 Evaluation -- 5.1 Datasets -- 5.2 Methodology -- 5.3 Monotonic Features Extraction -- 5.4 Models -- 5.5 Monotonicity Analysis -- 6 Conclusion and Future Work -- References -- Multiple-manifold Generation with an Ensemble GAN and Learned Noise Prior -- 1 Introduction -- 2 Related Work -- 3 Model -- 4 Experiments -- 4.1 Disconnected Manifolds -- 4.2 CelebA+Photo -- 4.3 Complex-But-Connected Image Dataset -- 4.4 CIFAR -- 5 Discussion -- References -- Simple, Efficient and Convenient Decentralized Multi-task Learning for Neural Networks -- 1 Introduction -- 2 The Method -- 2.1 Intuition -- 2.2 Description -- 3 Theoretical Analysis -- 4 Experiments -- 4.1 Setting -- 4.2 Results -- 5 Related Work -- 6 Conclusion -- References -- Deep Hybrid Neural Networks with Improved Weighted Word Embeddings for Sentiment Analysis -- 1 Introduction -- 2 Related Work -- 2.1 Sentiment Analysis -- 2.2 Vector Representation -- 3 Proposed Model -- 3.1 Embedding Layer -- 3.2 Convolution Layer -- 3.3 Max-Pooling and Dropout Layer -- 3.4 LSTM Layer -- 3.5 Fully-Connected Layer -- 3.6 Output Layer -- 4 Experiments and Results -- 4.1 Dataset Description -- 4.2 Parameters -- 4.3 Evaluation Metrics -- 4.4 Results and Discussion -- 5 Conclusion -- References.
Explaining Neural Networks by Decoding Layer Activations -- 1 Introduction -- 2 Method and Architecture -- 3 Theoretical Motivation of ClaDec -- 4 Assessing Interpretability and Fidelity -- 5 Evaluation -- 5.1 Qualitative Evaluation -- 5.2 Quantitative Evaluation -- 6 Related Work -- 7 Conclusions -- References -- Analogical Embedding for Analogy-Based Learning to Rank -- 1 Introduction -- 2 Analogy-Based Learning to Rank -- 3 Related Work -- 4 Analogical Embedding -- 4.1 Training the Embedding Network -- 4.2 Constructing Training Examples -- 5 Experiments -- 5.1 Data and Experimental Setup -- 5.2 Case Study 1: Analysing the Embedding Space -- 5.3 Case Study 2: Performance of able2rank -- 6 Conclusion -- References -- HORUS-NER: A Multimodal Named Entity Recognition Framework for Noisy Data -- 1 Introduction -- 2 Methodology and Features -- 3 Experimental Setup -- 4 Results and Discussion -- 5 Related Work -- 6 Conclusion -- References -- Modeling with Statistical Learning -- Incremental Search Space Construction for Machine Learning Pipeline Synthesis -- 1 Introduction -- 2 Preliminary and Related Work -- 3 DSWIZARD Methodology -- 3.1 Incremental Pipeline Structure Search -- 3.2 Hyperparameter Optimization -- 3.3 Meta-Learning -- 4 Experiments -- 4.1 Experiment Setup -- 4.2 Experiment Results -- 5 Conclusion -- References -- Adversarial Vulnerability of Active Transfer Learning -- 1 Introduction -- 2 Related Work -- 3 Attacking Active Transfer Learning -- 3.1 Threat Model -- 3.2 Feature Collision Attack -- 4 Implementation and Results -- 4.1 Active Transfer Learner Setup -- 4.2 Feature Collision Results -- 4.3 Impact on the Model -- 4.4 Hyper Parameters and Runtime -- 4.5 Adversarial Retraining Defense -- 5 Conclusion and Future Work -- References -- Revisiting Non-specific Syndromic Surveillance -- 1 Introduction. 2 Non-specific Syndromic Surveillance -- 2.1 Problem Definition -- 2.2 Evaluation -- 3 Machine Learning Algorithms -- 3.1 Data Mining Surveillance System (DMSS) -- 3.2 What Is Strange About Recent Events? (WSARE) -- 3.3 Eigenevent -- 3.4 Anomaly Detection Algorithms -- 4 Basic Statistical Approaches -- 5 Experiments and Results -- 5.1 Evaluation Setup -- 5.2 Preliminary Evaluation -- 5.3 Results -- 6 Conclusion -- References -- Gradient Ascent for Best Response Regression -- 1 Introduction -- 2 Best Response Regression -- 2.1 Shortcomings of the Approach by Ben-Porat and Tennenholtz -- 3 Notation -- 4 Gradient Ascent Approach -- 5 Experiments -- 6 Conclusions -- References -- Intelligent Structural Damage Detection: A Federated Learning Approach -- 1 Introduction -- 2 Background -- 2.1 Autoencoder Deep Neural Network -- 3 Federated Learning Augmented with Tensor Data Fusion for SHM -- 3.1 Data Structure -- 3.2 Problem Formulation in Federated Learning -- 3.3 Tensor Data Fusion -- 3.4 The Client-Server Learning Phase -- 4 Related Work -- 5 Experimental Results -- 5.1 Data Collection -- 5.2 Results and Discussions -- 6 Conclusions -- References -- Composite Surrogate for Likelihood-Free Bayesian Optimisation in High-Dimensional Settings of Activity-Based Transportation Models -- 1 Introduction -- 2 Materials and Methods -- 2.1 Preday ABM -- 2.2 Bayesian Optimisation for Likelihood-Free Inference -- 2.3 Limitations of BOLFI for Calibrating Preday ABM -- 3 BOLFI with Composite Surrogate Model -- 4 Results -- 5 Summary and Conclusions -- References -- Active Selection of Classification Features -- 1 Introduction -- 2 Related Work -- 3 Utility-Based Active Selection of Classification Features -- 3.1 Unsupervised, Imputation Variance-Based Variant (U-ASCF) -- 3.2 Supervised, Probabilistic Selection Variant (S-ASCF) -- 4 Experimental Results. 4.1 Comparative Results -- 4.2 Case Study -- 5 Conclusion -- References -- Feature Selection for Hierarchical Multi-label Classification -- 1 Introduction -- 2 Feature Selection -- 2.1 ReliefF -- 2.2 Information Gain -- 3 Related Work -- 4 Applying Feature Selection in HMC -- 4.1 Binary Relevance -- 4.2 Label Powerset -- 4.3 Our Proposal -- 5 Methodology -- 5.1 Datasets -- 5.2 Base Classifier -- 5.3 Evaluation Measures -- 6 Experiments and Discussion -- 7 Conclusion and Future Work -- References -- Bandit Algorithm for both Unknown Best Position and Best Item Display on Web Pages -- 1 Introduction -- 2 Related Work -- 3 Recommendation Setting -- 4 PB-MHB Algorithm -- 4.1 Sampling w.r.t. the Posterior Distribution -- 4.2 Overall Complexity -- 5 Experiments -- 5.1 Datasets -- 5.2 Competitors -- 5.3 Results -- 6 Conclusion -- References -- Performance Prediction for Hardware-Software Configurations: A Case Study for Video Games -- 1 Introduction -- 2 Learning Problem -- 3 Learning Model -- 3.1 Learning from Imprecise Observations -- 3.2 Enforcing Monotonicity Using a Penalty Term -- 3.3 Combined Loss -- 4 Case Study: Predicting FPS in Video Games -- 4.1 Dataset -- 4.2 Modeling Imprecise Observations -- 4.3 Experimental Design -- 4.4 Results -- 5 Related Work -- 6 Conclusion -- References -- AVATAR-Automated Feature Wrangling for Machine Learning -- 1 Introduction -- 2 Related Work -- 3 Data Wrangling for Machine Learning -- 3.1 Problem Statement -- 3.2 A Language for Feature Wrangling -- 3.3 Generating Arguments -- 4 Machine Learning for Feature Wrangling -- 4.1 Prune -- 4.2 Select -- 4.3 Evaluate -- 4.4 Wrangle -- 5 Evaluation -- 5.1 Wrangling New Features -- 5.2 Comparison with Humans -- 6 Conclusion and Future Work -- References -- Modeling Language and Graphs. Semantically Enriching Embeddings of Highly Inflectable Verbs for Improving Intent Detection in a Romanian Home Assistant Scenario -- 1 Introduction -- 2 Related Work -- 3 Home Assistant Scenario and Challenges -- 4 Proposed Solution -- 5 Empirical Evaluations -- 5.1 Experimental Setup -- 5.2 Results and Discussions -- 6 Conclusions, Limitations, and Further Work -- Appendix A Confusion matrices and histograms -- References -- BoneBert: A BERT-based Automated Information Extraction System of Radiology Reports for Bone Fracture Detection and Diagnosis -- 1 Introduction -- 2 Related Works -- 2.1 Rule-Based Approaches -- 2.2 Machine Learning Approaches -- 2.3 Hybrid Approaches -- 3 Methodology -- 3.1 Dataset -- 3.2 Information Extraction -- 3.3 Training and Evaluation -- 4 Experiments -- 4.1 Assertion Classification -- 4.2 Named Entity Recognition -- 5 Discussion -- 6 Conclusion -- References -- Linking the Dynamics of User Stance to the Structure of Online Discussions -- 1 Introduction -- 2 Related Work -- 3 The Dynamics of User Stance and Dataset -- 4 Forecast User Stance Dynamics -- 4.1 A Supervised Machine Learning Problem -- 4.2 Predictive Features -- 4.3 Learning Stance in Twitter -- 4.4 Predictive Setup -- 5 Results -- 6 Conclusion -- References -- Unsupervised Methods for the Study of Transformer Embeddings -- 1 Introduction -- 2 Related Work -- 3 Unsupervised Methods for Layer Analysis -- 3.1 Matrix and Vector Representation of Layers -- 3.2 Measuring the Correlations Between Layers -- 3.3 Clustering Layers -- 3.4 Interpreting Layers -- 4 Experiments -- 4.1 Datasets and Models Used -- 4.2 Investigating the Correlations Between Layers -- 4.3 Identifying Clusters of Layers -- 4.4 Qualitative Interpretation -- 4.5 Quantitative Interpretation Using Dimension Reduction -- 4.6 Results Validation Using a Clustering Performance Metric -- 5 Conclusion. References. |
| Record Nr. | UNINA-9910484642303321 |
| Cham, Switzerland : , : Springer, , [2021] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Advances in intelligent data analysis XIX : 19th International Symposium on Intelligent Data Analysis, IDA 2021, Porto, Portugal, April 26-28, 2021 : proceedings / / Pedro Henriques Abreu [and three others], (editors)
| Advances in intelligent data analysis XIX : 19th International Symposium on Intelligent Data Analysis, IDA 2021, Porto, Portugal, April 26-28, 2021 : proceedings / / Pedro Henriques Abreu [and three others], (editors) |
| Pubbl/distr/stampa | Cham, Switzerland : , : Springer, , [2021] |
| Descrizione fisica | 1 online resource (xvi, 454 pages) |
| Disciplina | 006.4 |
| Collana | Lecture notes in computer science |
| Soggetto topico |
Pattern recognition systems
Mathematical statistics Mathematical statistics - Data processing |
| ISBN | 3-030-74251-2 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Intro -- Preface -- Organization -- Contents -- Modeling with Neural Networks -- Hyperspherical Weight Uncertainty in Neural Networks -- 1 Introduction -- 2 Background: On Gaussian Distributions -- 3 Hypersphere Bayesian Neural Networks -- 4 Results -- 4.1 Non-linear Regression -- 4.2 Image Classification -- 4.3 Measuring Uncertainty -- 4.4 Active Learning Using Uncertainty Quantification -- 4.5 Variational Auto-encoders -- 5 Conclusion -- References -- Partially Monotonic Learning for Neural Networks -- 1 Introduction -- 2 Related Work -- 3 Monotonicity -- 4 Partially Monotonic Learning -- 4.1 Loss Function -- 5 Evaluation -- 5.1 Datasets -- 5.2 Methodology -- 5.3 Monotonic Features Extraction -- 5.4 Models -- 5.5 Monotonicity Analysis -- 6 Conclusion and Future Work -- References -- Multiple-manifold Generation with an Ensemble GAN and Learned Noise Prior -- 1 Introduction -- 2 Related Work -- 3 Model -- 4 Experiments -- 4.1 Disconnected Manifolds -- 4.2 CelebA+Photo -- 4.3 Complex-But-Connected Image Dataset -- 4.4 CIFAR -- 5 Discussion -- References -- Simple, Efficient and Convenient Decentralized Multi-task Learning for Neural Networks -- 1 Introduction -- 2 The Method -- 2.1 Intuition -- 2.2 Description -- 3 Theoretical Analysis -- 4 Experiments -- 4.1 Setting -- 4.2 Results -- 5 Related Work -- 6 Conclusion -- References -- Deep Hybrid Neural Networks with Improved Weighted Word Embeddings for Sentiment Analysis -- 1 Introduction -- 2 Related Work -- 2.1 Sentiment Analysis -- 2.2 Vector Representation -- 3 Proposed Model -- 3.1 Embedding Layer -- 3.2 Convolution Layer -- 3.3 Max-Pooling and Dropout Layer -- 3.4 LSTM Layer -- 3.5 Fully-Connected Layer -- 3.6 Output Layer -- 4 Experiments and Results -- 4.1 Dataset Description -- 4.2 Parameters -- 4.3 Evaluation Metrics -- 4.4 Results and Discussion -- 5 Conclusion -- References.
Explaining Neural Networks by Decoding Layer Activations -- 1 Introduction -- 2 Method and Architecture -- 3 Theoretical Motivation of ClaDec -- 4 Assessing Interpretability and Fidelity -- 5 Evaluation -- 5.1 Qualitative Evaluation -- 5.2 Quantitative Evaluation -- 6 Related Work -- 7 Conclusions -- References -- Analogical Embedding for Analogy-Based Learning to Rank -- 1 Introduction -- 2 Analogy-Based Learning to Rank -- 3 Related Work -- 4 Analogical Embedding -- 4.1 Training the Embedding Network -- 4.2 Constructing Training Examples -- 5 Experiments -- 5.1 Data and Experimental Setup -- 5.2 Case Study 1: Analysing the Embedding Space -- 5.3 Case Study 2: Performance of able2rank -- 6 Conclusion -- References -- HORUS-NER: A Multimodal Named Entity Recognition Framework for Noisy Data -- 1 Introduction -- 2 Methodology and Features -- 3 Experimental Setup -- 4 Results and Discussion -- 5 Related Work -- 6 Conclusion -- References -- Modeling with Statistical Learning -- Incremental Search Space Construction for Machine Learning Pipeline Synthesis -- 1 Introduction -- 2 Preliminary and Related Work -- 3 DSWIZARD Methodology -- 3.1 Incremental Pipeline Structure Search -- 3.2 Hyperparameter Optimization -- 3.3 Meta-Learning -- 4 Experiments -- 4.1 Experiment Setup -- 4.2 Experiment Results -- 5 Conclusion -- References -- Adversarial Vulnerability of Active Transfer Learning -- 1 Introduction -- 2 Related Work -- 3 Attacking Active Transfer Learning -- 3.1 Threat Model -- 3.2 Feature Collision Attack -- 4 Implementation and Results -- 4.1 Active Transfer Learner Setup -- 4.2 Feature Collision Results -- 4.3 Impact on the Model -- 4.4 Hyper Parameters and Runtime -- 4.5 Adversarial Retraining Defense -- 5 Conclusion and Future Work -- References -- Revisiting Non-specific Syndromic Surveillance -- 1 Introduction. 2 Non-specific Syndromic Surveillance -- 2.1 Problem Definition -- 2.2 Evaluation -- 3 Machine Learning Algorithms -- 3.1 Data Mining Surveillance System (DMSS) -- 3.2 What Is Strange About Recent Events? (WSARE) -- 3.3 Eigenevent -- 3.4 Anomaly Detection Algorithms -- 4 Basic Statistical Approaches -- 5 Experiments and Results -- 5.1 Evaluation Setup -- 5.2 Preliminary Evaluation -- 5.3 Results -- 6 Conclusion -- References -- Gradient Ascent for Best Response Regression -- 1 Introduction -- 2 Best Response Regression -- 2.1 Shortcomings of the Approach by Ben-Porat and Tennenholtz -- 3 Notation -- 4 Gradient Ascent Approach -- 5 Experiments -- 6 Conclusions -- References -- Intelligent Structural Damage Detection: A Federated Learning Approach -- 1 Introduction -- 2 Background -- 2.1 Autoencoder Deep Neural Network -- 3 Federated Learning Augmented with Tensor Data Fusion for SHM -- 3.1 Data Structure -- 3.2 Problem Formulation in Federated Learning -- 3.3 Tensor Data Fusion -- 3.4 The Client-Server Learning Phase -- 4 Related Work -- 5 Experimental Results -- 5.1 Data Collection -- 5.2 Results and Discussions -- 6 Conclusions -- References -- Composite Surrogate for Likelihood-Free Bayesian Optimisation in High-Dimensional Settings of Activity-Based Transportation Models -- 1 Introduction -- 2 Materials and Methods -- 2.1 Preday ABM -- 2.2 Bayesian Optimisation for Likelihood-Free Inference -- 2.3 Limitations of BOLFI for Calibrating Preday ABM -- 3 BOLFI with Composite Surrogate Model -- 4 Results -- 5 Summary and Conclusions -- References -- Active Selection of Classification Features -- 1 Introduction -- 2 Related Work -- 3 Utility-Based Active Selection of Classification Features -- 3.1 Unsupervised, Imputation Variance-Based Variant (U-ASCF) -- 3.2 Supervised, Probabilistic Selection Variant (S-ASCF) -- 4 Experimental Results. 4.1 Comparative Results -- 4.2 Case Study -- 5 Conclusion -- References -- Feature Selection for Hierarchical Multi-label Classification -- 1 Introduction -- 2 Feature Selection -- 2.1 ReliefF -- 2.2 Information Gain -- 3 Related Work -- 4 Applying Feature Selection in HMC -- 4.1 Binary Relevance -- 4.2 Label Powerset -- 4.3 Our Proposal -- 5 Methodology -- 5.1 Datasets -- 5.2 Base Classifier -- 5.3 Evaluation Measures -- 6 Experiments and Discussion -- 7 Conclusion and Future Work -- References -- Bandit Algorithm for both Unknown Best Position and Best Item Display on Web Pages -- 1 Introduction -- 2 Related Work -- 3 Recommendation Setting -- 4 PB-MHB Algorithm -- 4.1 Sampling w.r.t. the Posterior Distribution -- 4.2 Overall Complexity -- 5 Experiments -- 5.1 Datasets -- 5.2 Competitors -- 5.3 Results -- 6 Conclusion -- References -- Performance Prediction for Hardware-Software Configurations: A Case Study for Video Games -- 1 Introduction -- 2 Learning Problem -- 3 Learning Model -- 3.1 Learning from Imprecise Observations -- 3.2 Enforcing Monotonicity Using a Penalty Term -- 3.3 Combined Loss -- 4 Case Study: Predicting FPS in Video Games -- 4.1 Dataset -- 4.2 Modeling Imprecise Observations -- 4.3 Experimental Design -- 4.4 Results -- 5 Related Work -- 6 Conclusion -- References -- AVATAR-Automated Feature Wrangling for Machine Learning -- 1 Introduction -- 2 Related Work -- 3 Data Wrangling for Machine Learning -- 3.1 Problem Statement -- 3.2 A Language for Feature Wrangling -- 3.3 Generating Arguments -- 4 Machine Learning for Feature Wrangling -- 4.1 Prune -- 4.2 Select -- 4.3 Evaluate -- 4.4 Wrangle -- 5 Evaluation -- 5.1 Wrangling New Features -- 5.2 Comparison with Humans -- 6 Conclusion and Future Work -- References -- Modeling Language and Graphs. Semantically Enriching Embeddings of Highly Inflectable Verbs for Improving Intent Detection in a Romanian Home Assistant Scenario -- 1 Introduction -- 2 Related Work -- 3 Home Assistant Scenario and Challenges -- 4 Proposed Solution -- 5 Empirical Evaluations -- 5.1 Experimental Setup -- 5.2 Results and Discussions -- 6 Conclusions, Limitations, and Further Work -- Appendix A Confusion matrices and histograms -- References -- BoneBert: A BERT-based Automated Information Extraction System of Radiology Reports for Bone Fracture Detection and Diagnosis -- 1 Introduction -- 2 Related Works -- 2.1 Rule-Based Approaches -- 2.2 Machine Learning Approaches -- 2.3 Hybrid Approaches -- 3 Methodology -- 3.1 Dataset -- 3.2 Information Extraction -- 3.3 Training and Evaluation -- 4 Experiments -- 4.1 Assertion Classification -- 4.2 Named Entity Recognition -- 5 Discussion -- 6 Conclusion -- References -- Linking the Dynamics of User Stance to the Structure of Online Discussions -- 1 Introduction -- 2 Related Work -- 3 The Dynamics of User Stance and Dataset -- 4 Forecast User Stance Dynamics -- 4.1 A Supervised Machine Learning Problem -- 4.2 Predictive Features -- 4.3 Learning Stance in Twitter -- 4.4 Predictive Setup -- 5 Results -- 6 Conclusion -- References -- Unsupervised Methods for the Study of Transformer Embeddings -- 1 Introduction -- 2 Related Work -- 3 Unsupervised Methods for Layer Analysis -- 3.1 Matrix and Vector Representation of Layers -- 3.2 Measuring the Correlations Between Layers -- 3.3 Clustering Layers -- 3.4 Interpreting Layers -- 4 Experiments -- 4.1 Datasets and Models Used -- 4.2 Investigating the Correlations Between Layers -- 4.3 Identifying Clusters of Layers -- 4.4 Qualitative Interpretation -- 4.5 Quantitative Interpretation Using Dimension Reduction -- 4.6 Results Validation Using a Clustering Performance Metric -- 5 Conclusion. References. |
| Record Nr. | UNISA-996464382703316 |
| Cham, Switzerland : , : Springer, , [2021] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. di Salerno | ||
| ||
Advances in Intelligent Data Analysis XXI : 21st International Symposium on Intelligent Data Analysis, IDA 2023, Louvain-La-Neuve, Belgium, April 12-14, 2023, Proceedings / / Bruno Crémilleux, Sibylle Hess, and Siegfried Nijssen, editors
| Advances in Intelligent Data Analysis XXI : 21st International Symposium on Intelligent Data Analysis, IDA 2023, Louvain-La-Neuve, Belgium, April 12-14, 2023, Proceedings / / Bruno Crémilleux, Sibylle Hess, and Siegfried Nijssen, editors |
| Edizione | [First edition.] |
| Pubbl/distr/stampa | Cham, Switzerland : , : Springer, Springer Nature Switzerland AG, , [2023] |
| Descrizione fisica | 1 online resource (514 pages) |
| Disciplina | 519.5 |
| Collana | Lecture Notes in Computer Science Series |
| Soggetto topico |
Mathematical statistics
Mathematical statistics - Data processing Pattern recognition systems |
| ISBN |
9783031300479
9783031300462 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Contextual Word Embeddings Clustering through Multiway Analysis: A Comparative Study -- Transferable Deep Metric Learning for Clustering -- Spatial Graph Convolution Neural Networks for Water Distribution Systems -- Data-Centric Perspective on Explainability versus Performance Trade-off -- Towards Data Science Design Patterns -- Diverse Paraphrasing with Insertion Models for Few-Shot Intent Detection -- LEMON: Alternative Sampling for More Faithful Explanation through Local Surrogate Models -- GASTeN: Generative Adversarial Stress Test Networks -- Learning Permutation-Invariant Embeddings for Description Logic Concepts -- Diffusion Transport Alignment -- Mind the Gap: Measuring Generalization Performance Across Multiple Objectives -- Effects of Locality and Rule Language on Explanations for Knowledge Graph Embeddings -- Shapley Values with Uncertain Value Functions. -Revised Conditional t-SNE: Looking Beyond the Nearest Neighbors -- On the Change of Decision Boundary and Loss in Learning with Concept Drift -- AID4HAI: Automatic Idea Detection for Healthcare-Associated Infections from Twitter, A Framework based on Active Learning and Transfer Learning -- Explanations for Itemset Mining by Constraint Programming: A Case Study using ChEMBL data -- Translated Texts Under the Lens: From Machine Translation Detection to Source Language Identification -- Geolet: An Interpretable Model for Trajectory Classification -- An investigation of structures responsible for gender bias in BERT and DistilBERT -- Discovering diverse top-k characteristic lists -- Online Influence Forest for Streaming Anomaly Detection -- APs: a proxemic framework for social media interactions modeling and analysis -- User Authentication via Multifaceted Mouse Movementsand Outlier Exposure -- Explaining Black Box Reinforcement Learning Agents Through Counterfactual Policies -- A GNN-based Architecture for Group Detection from spatio-temporal Trajectory Data -- Discovering Rule Lists with Preferred Variables -- Don’t Start Your Data Labeling from Scratch: OpSaLa - Optimized Data Sampling Before Labeling -- The Other Side of Compression: Measuring Bias in Pruned Transformers -- Dropping incomplete records is (not so) straightforward -- Meta-Learning for Automated Selection of Anomaly Detectors for Semi-Supervised Datasets -- Should We Consider On-Demand Analysis in Scale-Free Networks? -- ROCKAD: Transferring ROCKET to whole time series anomaly detection -- Out-of-Distribution Generalisation with Symmetry-Based Disentangled Representations -- Forecasting Electricity Prices: an Optimize then Predict-based approach -- A Similarity-Guided Framework for Error-Driven Discovery of Patient Neighbourhoods in EMA Data -- QBERT: Generalist Model for Processing Questions -- On Compositionality in Data Embedding. |
| Altri titoli varianti |
Advances in Intelligent Data Analysis 21
Advances in Intelligent Data Analysis Twenty-one |
| Record Nr. | UNISA-996517751403316 |
| Cham, Switzerland : , : Springer, Springer Nature Switzerland AG, , [2023] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. di Salerno | ||
| ||
Advances in Intelligent Data Analysis XXI : 21st International Symposium on Intelligent Data Analysis, IDA 2023, Louvain-La-Neuve, Belgium, April 12-14, 2023, Proceedings / / Bruno Crémilleux, Sibylle Hess, and Siegfried Nijssen, editors
| Advances in Intelligent Data Analysis XXI : 21st International Symposium on Intelligent Data Analysis, IDA 2023, Louvain-La-Neuve, Belgium, April 12-14, 2023, Proceedings / / Bruno Crémilleux, Sibylle Hess, and Siegfried Nijssen, editors |
| Edizione | [First edition.] |
| Pubbl/distr/stampa | Cham, Switzerland : , : Springer, Springer Nature Switzerland AG, , [2023] |
| Descrizione fisica | 1 online resource (514 pages) |
| Disciplina | 519.5 |
| Collana | Lecture Notes in Computer Science Series |
| Soggetto topico |
Mathematical statistics
Mathematical statistics - Data processing Pattern recognition systems |
| ISBN |
9783031300479
9783031300462 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Contextual Word Embeddings Clustering through Multiway Analysis: A Comparative Study -- Transferable Deep Metric Learning for Clustering -- Spatial Graph Convolution Neural Networks for Water Distribution Systems -- Data-Centric Perspective on Explainability versus Performance Trade-off -- Towards Data Science Design Patterns -- Diverse Paraphrasing with Insertion Models for Few-Shot Intent Detection -- LEMON: Alternative Sampling for More Faithful Explanation through Local Surrogate Models -- GASTeN: Generative Adversarial Stress Test Networks -- Learning Permutation-Invariant Embeddings for Description Logic Concepts -- Diffusion Transport Alignment -- Mind the Gap: Measuring Generalization Performance Across Multiple Objectives -- Effects of Locality and Rule Language on Explanations for Knowledge Graph Embeddings -- Shapley Values with Uncertain Value Functions. -Revised Conditional t-SNE: Looking Beyond the Nearest Neighbors -- On the Change of Decision Boundary and Loss in Learning with Concept Drift -- AID4HAI: Automatic Idea Detection for Healthcare-Associated Infections from Twitter, A Framework based on Active Learning and Transfer Learning -- Explanations for Itemset Mining by Constraint Programming: A Case Study using ChEMBL data -- Translated Texts Under the Lens: From Machine Translation Detection to Source Language Identification -- Geolet: An Interpretable Model for Trajectory Classification -- An investigation of structures responsible for gender bias in BERT and DistilBERT -- Discovering diverse top-k characteristic lists -- Online Influence Forest for Streaming Anomaly Detection -- APs: a proxemic framework for social media interactions modeling and analysis -- User Authentication via Multifaceted Mouse Movementsand Outlier Exposure -- Explaining Black Box Reinforcement Learning Agents Through Counterfactual Policies -- A GNN-based Architecture for Group Detection from spatio-temporal Trajectory Data -- Discovering Rule Lists with Preferred Variables -- Don’t Start Your Data Labeling from Scratch: OpSaLa - Optimized Data Sampling Before Labeling -- The Other Side of Compression: Measuring Bias in Pruned Transformers -- Dropping incomplete records is (not so) straightforward -- Meta-Learning for Automated Selection of Anomaly Detectors for Semi-Supervised Datasets -- Should We Consider On-Demand Analysis in Scale-Free Networks? -- ROCKAD: Transferring ROCKET to whole time series anomaly detection -- Out-of-Distribution Generalisation with Symmetry-Based Disentangled Representations -- Forecasting Electricity Prices: an Optimize then Predict-based approach -- A Similarity-Guided Framework for Error-Driven Discovery of Patient Neighbourhoods in EMA Data -- QBERT: Generalist Model for Processing Questions -- On Compositionality in Data Embedding. |
| Altri titoli varianti |
Advances in Intelligent Data Analysis 21
Advances in Intelligent Data Analysis Twenty-one |
| Record Nr. | UNINA-9910686782303321 |
| Cham, Switzerland : , : Springer, Springer Nature Switzerland AG, , [2023] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Advances in Knowledge Discovery and Data Mining [[electronic resource] ] : 13th Pacific-Asia Conference, PAKDD 2009 Bangkok, Thailand, April 27-30, 2009 Proceedings / / edited by Thanaruk Theeramunkong, Boonserm Kijsirikul, Nick Cercone, Tu-Bao Ho
| Advances in Knowledge Discovery and Data Mining [[electronic resource] ] : 13th Pacific-Asia Conference, PAKDD 2009 Bangkok, Thailand, April 27-30, 2009 Proceedings / / edited by Thanaruk Theeramunkong, Boonserm Kijsirikul, Nick Cercone, Tu-Bao Ho |
| Edizione | [1st ed. 2009.] |
| Pubbl/distr/stampa | Berlin, Heidelberg : , : Springer Berlin Heidelberg : , : Imprint : Springer, , 2009 |
| Descrizione fisica | 1 online resource (XXIV, 1076 p.) |
| Disciplina | 006.3 |
| Collana | Lecture Notes in Artificial Intelligence |
| Soggetto topico |
Artificial intelligence
Data mining Information storage and retrieval Mathematical statistics Multimedia information systems Application software Artificial Intelligence Data Mining and Knowledge Discovery Information Storage and Retrieval Probability and Statistics in Computer Science Multimedia Information Systems Computer Appl. in Administrative Data Processing |
| ISBN | 3-642-01307-4 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Keynote Speeches -- Regular Papers -- Short Papers. |
| Record Nr. | UNISA-996466015503316 |
| Berlin, Heidelberg : , : Springer Berlin Heidelberg : , : Imprint : Springer, , 2009 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. di Salerno | ||
| ||
