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The 3rd International Workshop on Intelligent Data Analysis and Management / / Lorna Uden ...[et. al.], editors
The 3rd International Workshop on Intelligent Data Analysis and Management / / Lorna Uden ...[et. al.], editors
Edizione [1st ed. 2013.]
Pubbl/distr/stampa Dordrecht, : Springer Science, 2013
Descrizione fisica 1 online resource (x, 132 pages) : illustrations (some color)
Disciplina 004
Altri autori (Persone) UdenLorna <1946->
Collana Springer proceedings in complexity
Soggetto topico Mathematical statistics - Data processing
Artificial intelligence
ISBN 94-007-7293-9
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto An Information Quality (InfoQ) Framework for Ex-Ante and Ex-Post Evaluation of Empirical Studies -- Memory-Aware Mining of Indirect Associations over Data Streams -- Graph-based batch mode active learning -- One Pass Outlier Detection for Streaming Categorical Data -- Measuring of QoE for Cloud Applications -- Mining Weighted Partial Periodic Patterns -- Edge Selection for Degree Anonymization on K Shortest Paths -- K-Neighborhood Shortest Path Privacy in the Cloud -- The Framework of Information Processing Network for Supply Chain Innovation in Big Data Era -- Website Navigation Recommendation Based on Reinforcement Learning Technique -- An Approach for Hate Groups Detection in Facebook -- Toward Crowdsourcing Data Mining -- Wireless Security Analysis Using War Drive Investigation in Kaohsiung Areas -- Guanxi buying in the social media environment -- Introspection of unauthorized sharing on social networking sites.
Altri titoli varianti Third International Workshop on Intelligent Data Analysis and Management
Record Nr. UNINA-9910437983003321
Dordrecht, : Springer Science, 2013
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Advances in intelligent data analysis IX : 9th International Symposium, IDA 2010, Tucson, AZ, USA, May 19-21, 2010 : proceedings / / Paul R. Cohen, Niall M. Adams, Michael R. Berthold, (eds.)
Advances in intelligent data analysis IX : 9th International Symposium, IDA 2010, Tucson, AZ, USA, May 19-21, 2010 : proceedings / / Paul R. Cohen, Niall M. Adams, Michael R. Berthold, (eds.)
Edizione [1st ed.]
Pubbl/distr/stampa New York, : Springer, 2010
Descrizione fisica 1 online resource (XIII, 260 p. 89 illus.)
Disciplina 519.5
Collana Lecture notes in computer science
Soggetto topico Mathematical statistics
Mathematical statistics - Data processing
Expert systems (Computer science)
ISBN 1-280-38655-X
9786613564474
3-642-13062-3
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Changing the Focus of the IDA Symposium -- Changing the Focus of the IDA Symposium -- Invited Papers -- Graph Identification -- Intelligent Data Analysis of Intelligent Systems -- Selected Contributions -- Measurement and Dynamical Analysis of Computer Performance Data -- Recursive Sequence Mining to Discover Named Entity Relations -- Integration and Dissemination of Citizen Reported and Seismically Derived Earthquake Information via Social Network Technologies -- Detecting Leukemia (AML) Blood Cells Using Cellular Automata and Heuristic Search -- Oracle Coached Decision Trees and Lists -- Statistical Modelling for Data from Experiments with Short Hairpin RNAs -- InfraWatch: Data Management of Large Systems for Monitoring Infrastructural Performance -- Deterministic Finite Automata in the Detection of EEG Spikes and Seizures -- Bipartite Graphs for Monitoring Clusters Transitions -- Data Mining for Modeling Chiller Systems in Data Centers -- The Applications of Artificial Neural Networks in the Identification of Quantitative Structure-Activity Relationships for Chemotherapeutic Drug Carcinogenicity -- Image Approach towards Document Mining in Neuroscientific Publications -- Similarity Kernels for Nearest Neighbor-Based Outlier Detection -- End-to-End Support for Dating Paleolandforms -- Spatial Variable Importance Assessment for Yield Prediction in Precision Agriculture -- Selecting the Links in BisoNets Generated from Document Collections -- Novelty Detection in Projected Spaces for Structural Health Monitoring -- A Framework for Path-Oriented Network Simplification -- A Data-Driven Paradigm to Understand Multimodal Communication in Human-Human and Human-Robot Interaction -- Using CAPTCHAs to Index Cultural Artifacts.
Record Nr. UNINA-9910483592603321
New York, : Springer, 2010
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Advances in intelligent data analysis VI : 6th International Symposium on Intelligent Data Analysis, IDA 2005, Madrid, Spain, September 8-10, 2005 : proceedings / / A. Fazel Famili ... [et al.] (eds.)
Advances in intelligent data analysis VI : 6th International Symposium on Intelligent Data Analysis, IDA 2005, Madrid, Spain, September 8-10, 2005 : proceedings / / A. Fazel Famili ... [et al.] (eds.)
Edizione [1st ed. 2005.]
Pubbl/distr/stampa Berlin ; ; New York, : Springer, c2005
Descrizione fisica 1 online resource (XIV, 534 p.)
Disciplina 006.3/3
Altri autori (Persone) FamiliA. Fazel
Collana Lecture notes in computer science
Soggetto topico Mathematical statistics
Mathematical statistics - Data processing
Expert systems (Computer science)
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.
Altri titoli varianti 6th International Symposium on Intelligent Data Analysis
Sixth International Symposium on Intelligent Data Analysis
International Symposium on Intelligent Data Analysis
IDA 2005
Advances in intelligent data analysis 6
Record Nr. UNINA-9910483204003321
Berlin ; ; New York, : Springer, c2005
Materiale a stampa
Lo trovi qui: Univ. Federico II
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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
Opac: Controlla la disponibilità qui
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
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Advances in intelligent data analysis VIII : 8th international symposium on intelligent data analysis, IDA 2009, Lyon, France, August 31 - September 2, 2009. Proceedings / / Niall M. Adams, Celine Robardet, Arno Siebes, Jean-Francois Boulicaut (eds.)
Advances in intelligent data analysis VIII : 8th international symposium on intelligent data analysis, IDA 2009, Lyon, France, August 31 - September 2, 2009. Proceedings / / Niall M. Adams, Celine Robardet, Arno Siebes, Jean-Francois Boulicaut (eds.)
Edizione [1st ed. 2009.]
Pubbl/distr/stampa Berlin ; ; Heidelberg, : Springer-Verlag, 2009
Descrizione fisica 1 online resource (XIII, 418 p.)
Disciplina 006.31222gerDNB
Altri autori (Persone) AdamsNiall M. <1968->
RobardetCeline
SiebesArno
BoulicautJean-Francois
Collana Lecture notes in computer science
Soggetto topico Mathematical statistics - Data processing
Expert systems (Computer science)
ISBN 3-642-03915-4
Classificazione DAT 703f
MAT 620f
SS 4800
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Invited Papers -- Intelligent Data Analysis in the 21st Century -- Analyzing the Localization of Retail Stores with Complex Systems Tools -- Selected Contributions 1 (Long Talks) -- Change (Detection) You Can Believe in: Finding Distributional Shifts in Data Streams -- Exploiting Data Missingness in Bayesian Network Modeling -- DEMScale: Large Scale MDS Accounting for a Ridge Operator and Demographic Variables -- How to Control Clustering Results? Flexible Clustering Aggregation -- Compensation of Translational Displacement in Time Series Clustering Using Cross Correlation -- Context-Based Distance Learning for Categorical Data Clustering -- Semi-supervised Text Classification Using RBF Networks -- Improving k-NN for Human Cancer Classification Using the Gene Expression Profiles -- Subgroup Discovery for Test Selection: A Novel Approach and Its Application to Breast Cancer Diagnosis -- Trajectory Voting and Classification Based on Spatiotemporal Similarity in Moving Object Databases -- Leveraging Call Center Logs for Customer Behavior Prediction -- Condensed Representation of Sequential Patterns According to Frequency-Based Measures -- ART-Based Neural Networks for Multi-label Classification -- Two-Way Grouping by One-Way Topic Models -- Selecting and Weighting Data for Building Consensus Gene Regulatory Networks -- Incremental Bayesian Network Learning for Scalable Feature Selection -- Feature Extraction and Selection from Vibration Measurements for Structural Health Monitoring -- Zero-Inflated Boosted Ensembles for Rare Event Counts -- Selected Contributions 2 (Short Talks) -- Mining the Temporal Dimension of the Information Propagation -- Adaptive Learning from Evolving Data Streams -- An Application of Intelligent Data Analysis Techniques to a Large Software Engineering Dataset -- Which Distance for the Identification and the Differentiation of Cell-Cycle Expressed Genes? -- Ontology-Driven KDD Process Composition -- Mining Frequent Gradual Itemsets from Large Databases -- Selecting Computer Architectures by Means of Control-Flow-Graph Mining -- Visualization-Driven Structural and Statistical Analysis of Turbulent Flows -- Distributed Algorithm for Computing Formal Concepts Using Map-Reduce Framework -- Multi-Optimisation Consensus Clustering -- Improving Time Series Forecasting by Discovering Frequent Episodes in Sequences -- Measure of Similarity and Compactness in Competitive Space -- Bayesian Solutions to the Label Switching Problem -- Efficient Vertical Mining of Frequent Closures and Generators -- Isotonic Classification Trees.
Record Nr. UNINA-9910483134103321
Berlin ; ; Heidelberg, : Springer-Verlag, 2009
Materiale a stampa
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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 / / 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
Opac: Controlla la disponibilità qui
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
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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
Opac: Controlla la disponibilità qui
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
Opac: Controlla la disponibilità qui