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 | ||
![]() | ||
Lo trovi qui: Univ. Federico II | ||
|
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 | ||
![]() | ||
Lo trovi qui: Univ. Federico II | ||
|
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 | ||
![]() | ||
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) |
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] | ||
![]() | ||
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) |
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] | ||
![]() | ||
Lo trovi qui: Univ. di Salerno | ||
|
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 | ||
![]() | ||
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) |
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] | ||
![]() | ||
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) |
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] | ||
![]() | ||
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 |
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] | ||
![]() | ||
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 |
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] | ||
![]() | ||
Lo trovi qui: Univ. Federico II | ||
|