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Biblioteca

MARC Lista (tabellare)
Advanced Computing Technologies and Applications : Proceedings of 2nd International Conference on Advanced Computing Technologies and Applications—ICACTA 2020 / / edited by Hari Vasudevan, Antonis Michalas, Narendra Shekokar, Meera Narvekar
Advanced Computing Technologies and Applications : Proceedings of 2nd International Conference on Advanced Computing Technologies and Applications—ICACTA 2020 / / edited by Hari Vasudevan, Antonis Michalas, Narendra Shekokar, Meera Narvekar
Edizione [1st ed. 2020.]
Pubbl/distr/stampa Singapore : , : Springer Nature Singapore : , : Imprint : Springer, , 2020
Descrizione fisica 1 online resource (XVIII, 701 p. 336 illus., 240 illus. in color.)
Disciplina 004
Collana Algorithms for Intelligent Systems
Soggetto topico Engineering mathematics
Engineering - Data processing
Mathematical statistics - Data processing
Computer science - Mathematics
Robotics
Mathematical and Computational Engineering Applications
Statistics and Computing
Mathematics of Computing
ISBN 981-15-3242-7
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Career counselling chatbot using cognitive science and artificial intelligence -- IndoorNet: Generating Indoor Layouts from a Single Panorama Image -- Area Analysis for Dengue Prediction -- Chest pathology detection using medical imaging -- Proposed Infrastructure for Census Enumeration and Internet Voting Application in Digital India with Multichain Blockchain -- Deep Learning Challenges in Medical Imaging -- A Brief Survey of Sentiment Analysis -- Efficacy Analysis of Technology Approaches towards Auto Assignment of Clinical Codes to the US Patient Medical Record -- Reference Model Storage Covert channel for Secure Communications -- Automated Scoring System for Online Discussion Forum using Machine Learning and Similarity Measure -- Blockchain Powered Real Estate System -- A Novel Design for Voice-Enabled Home Automation and Personalized Recommendation System.
Record Nr. UNINA-9910403766903321
Singapore : , : Springer Nature Singapore : , : Imprint : Springer, , 2020
Materiale a stampa
Lo trovi qui: Univ. Federico II
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Advanced R : Data Programming and the Cloud / / by Matt Wiley, Joshua F. Wiley
Advanced R : Data Programming and the Cloud / / by Matt Wiley, Joshua F. Wiley
Autore Wiley Matt
Edizione [1st ed. 2016.]
Pubbl/distr/stampa Berkeley, CA : , : Apress : , : Imprint : Apress, , 2016
Descrizione fisica 1 online resource (XIX, 279 p. 77 illus., 40 illus. in color.)
Disciplina 005.13
Soggetto topico Compilers (Computer programs)
Computer science - Mathematics
Mathematical statistics
Mathematical statistics - Data processing
Computer programming
Compilers and Interpreters
Probability and Statistics in Computer Science
Statistics and Computing
Programming Techniques
ISBN 9781484220771
1484220773
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto 1.Programming Basics -- 2.Programming Utilities -- 3.Loops, flow control, and *apply functions -- 4.Writing Functions -- 5.Writing Classes and Methods -- 6.Writing a Package -- 7.Data Management using data.table -- 8.Data Munging With data.table -- 9.Other Tools for Data Management -- 10.Reading Big Data(bases) -- 11.Getting a Cloud -- 12.Ubuntu for Windows Users -- 13.Every Cloud has a Shiny lining -- 14.Shiny Dashboard Sampler -- 15.Dynamic Reports and the Cloud -- References.
Record Nr. UNINA-9910151576903321
Wiley Matt  
Berkeley, CA : , : Apress : , : Imprint : Apress, , 2016
Materiale a stampa
Lo trovi qui: Univ. Federico II
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Advanced R 4 Data Programming and the Cloud : Using PostgreSQL, AWS, and Shiny / / by Matt Wiley, Joshua F. Wiley
Advanced R 4 Data Programming and the Cloud : Using PostgreSQL, AWS, and Shiny / / by Matt Wiley, Joshua F. Wiley
Autore Wiley Matt
Edizione [2nd ed. 2020.]
Pubbl/distr/stampa Berkeley, CA : , : Apress : , : Imprint : Apress, , 2020
Descrizione fisica 1 online resource (XIII, 433 p. 65 illus., 9 illus. in color.)
Disciplina 005.133
Soggetto topico Compilers (Computer programs)
Computer science - Mathematics
Mathematical statistics
Mathematical statistics - Data processing
Computer programming
Compilers and Interpreters
Probability and Statistics in Computer Science
Statistics and Computing
Programming Techniques
ISBN 9781484259733
1484259734
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto 1. Programming Basics -- 2. Programming Utilities -- 3. Programming Automation -- 4. Writing Functions -- 5. Writing Classes and Methods -- 6. Writing Packages -- 7. Introduction to data.table -- 8. Advanced data.table -- 9. Other Data Management Packages -- 10. Reading Big Data -- 11. Getting Your Cloud -- 12. Cloud Ubuntu for Windows Users -- 13. Every Cloud has a Shiny lining -- 14. Shiny Dashboard Sampler -- 15. Dynamic Reports and the Cloud -- Bibliography.
Record Nr. UNINA-9910411930303321
Wiley Matt  
Berkeley, CA : , : Apress : , : Imprint : Apress, , 2020
Materiale a stampa
Lo trovi qui: Univ. Federico II
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Advanced Sampling Methods / / by Raosaheb Latpate, Jayant Kshirsagar, Vinod Kumar Gupta, Girish Chandra
Advanced Sampling Methods / / by Raosaheb Latpate, Jayant Kshirsagar, Vinod Kumar Gupta, Girish Chandra
Autore Latpate Raosaheb
Edizione [1st ed. 2021.]
Pubbl/distr/stampa Singapore : , : Springer Nature Singapore : , : Imprint : Springer, , 2021
Descrizione fisica 1 online resource (XVII, 301 p. 23 illus., 13 illus. in color.)
Disciplina 519.52
Soggetto topico Statistics
Mathematical statistics - Data processing
Statistical Theory and Methods
Bayesian Inference
Statistics and Computing
ISBN 9789811606229
9811606226
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto -1. Introduction -- 2. Simple Random Sampling -- 3. Stratied Random Sampling -- 4. Cluster Sampling -- 5. Double Sampling -- 6. Probability Proportional to Size Sampling -- 7. Systematic Sampling -- 8. Resampling Techniques -- 9. Adaptive Cluster Sampling -- 10. Two-Stage Adaptive Cluster Sampling -- 11. Adaptive Cluster Double Sampling -- 12. Inverse Adaptive Cluster Sampling -- 13. Two Stage Inverse Adaptive Cluster Sampling -- 14. Stratified Inverse Adaptive Cluster Sampling -- 15. Negative Adaptive Cluster Sampling -- 16. Negative Adaptive Cluster Double Sampling -- 17. Two- Stage Negative Adaptive Cluster Sampling -- 18. Balanced and Unbalanced Ranked Set Sampling -- 19. Ranked Set Sampling in Other Parameter Estimation and Non-Parametric Inference -- 20. Important Versions of Ranked Set Sampling -- 21. Sampling Errors.
Record Nr. UNINA-9910484590903321
Latpate Raosaheb  
Singapore : , : Springer Nature Singapore : , : Imprint : Springer, , 2021
Materiale a stampa
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Advances and Challenges in Parametric and Semi-parametric Analysis for Correlated Data : Proceedings of the 2015 International Symposium in Statistics / / edited by Brajendra C. Sutradhar
Advances and Challenges in Parametric and Semi-parametric Analysis for Correlated Data : Proceedings of the 2015 International Symposium in Statistics / / edited by Brajendra C. Sutradhar
Edizione [1st ed. 2016.]
Pubbl/distr/stampa Cham : , : Springer International Publishing : , : Imprint : Springer, , 2016
Descrizione fisica 1 online resource (XIX, 256 p. 12 illus., 6 illus. in color.)
Disciplina 519.5
Collana Lecture Notes in Statistics - Proceedings
Soggetto topico Statistics
Mathematical statistics - Data processing
Statistical Theory and Methods
Statistics and Computing
ISBN 3-319-31260-X
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Record Nr. UNINA-9910254077003321
Cham : , : Springer International Publishing : , : Imprint : Springer, , 2016
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. UNISA-996465748403316
Berlin ; ; Heidelberg : , : Springer, , [2007]
Materiale a stampa
Lo trovi qui: Univ. di Salerno
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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. 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]
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Advances in Statistical Models for Data Analysis / / edited by Isabella Morlini, Tommaso Minerva, Maurizio Vichi
Advances in Statistical Models for Data Analysis / / edited by Isabella Morlini, Tommaso Minerva, Maurizio Vichi
Edizione [1st ed. 2015.]
Pubbl/distr/stampa Cham : , : Springer International Publishing : , : Imprint : Springer, , 2015
Descrizione fisica 1 online resource (264 p.)
Disciplina 519.5
Collana Studies in Classification, Data Analysis, and Knowledge Organization
Soggetto topico Statistics
Mathematical statistics - Data processing
Social sciences - Statistical methods
Statistical Theory and Methods
Statistics and Computing
Statistics in Business, Management, Economics, Finance, Insurance
Statistics in Engineering, Physics, Computer Science, Chemistry and Earth Sciences
Statistics in Social Sciences, Humanities, Law, Education, Behavorial Sciences, Public Policy
ISBN 3-319-17377-4
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Using the dglars Package to Estimate a Sparse Generalized Linear Model -- A Depth function for Geostatistical Functional Data -- Robust Clustering of EU Banking Data -- Sovereign Risk and Contagion Effects in the Eurozone: a Bayesian Stochastic Correlation Model -- Female Labour Force Participation and Selection Effect: Southern vs Eastern European Countries -- Asymptotics in Survey Sampling for High Entropy Sampling Design -- A Note On the Use of Recursive Partitioning in Causal Inference -- Meta-Analysis of Poll Accuracy Measures: A Multilevel Approach -- Families of Parsimonious Finite Mixtures of Regression Models -- Quantile Regression for Clustering and Modeling Data -- Non-metric MDS Consensus Community Detection -- The performance of the Gradient-like Influence Measure in Generalized Linear Mixed Models -- New Flexible Probability Distributions for Ranking Data -- Robust Estimation of Regime Switching Models -- Incremental Visualization of Categorical Data -- A new Proposal for Tree Model Selection and Visualization -- Object-Oriented Bayesian Network to Deal with Measurement Error in Household Surveys -- Comparing Fuzzy and Multidimensional Methods to Evaluate Well-being in European Regions -- Cluster Analysis of Three-way Atmospheric Data -- Asymmetric CLUster Analysis Based on SKEW-symmetry: ACLUSKEW -- Parsimonious Generalized Linear Gaussian Cluster-Weighted Models -- New perspectives for the MDC Index in Social Research Fields -- Clustering Methods for Ordinal Data: A Comparison Between Standard and New Approaches -- Novelty Detection with One-class Support Vector Machines -- Using Discrete-time  Multi-State Models to Analyze  Students' University Pathways.
Record Nr. UNINA-9910300242403321
Cham : , : Springer International Publishing : , : Imprint : Springer, , 2015
Materiale a stampa
Lo trovi qui: Univ. Federico II
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Algorithmic Decision Making with Python Resources : From Multicriteria Performance Records to Decision Algorithms via Bipolar-Valued Outranking Digraphs / / by Raymond Bisdorff
Algorithmic Decision Making with Python Resources : From Multicriteria Performance Records to Decision Algorithms via Bipolar-Valued Outranking Digraphs / / by Raymond Bisdorff
Autore Bisdorff Raymond
Edizione [1st ed. 2022.]
Pubbl/distr/stampa Cham : , : Springer International Publishing : , : Imprint : Springer, , 2022
Descrizione fisica 1 online resource (366 pages)
Disciplina 005.133
658.4033
Collana International Series in Operations Research & Management Science
Soggetto topico Operations research
Graph theory
Computer science - Mathematics
Mathematical statistics - Data processing
Operations Research and Decision Theory
Graph Theory
Mathematical Applications in Computer Science
Statistics and Computing
ISBN 9783030909284
9783030909277
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Part I: Introduction to the DIGRAPH3 Python Resources -- 1. Working with the DIGRAPH3 Python Resources -- 2. Working with Bipolar-Valued Digraphs -- 3. Working with Outranking Digraphs -- Part II: Evaluation Models and Decision Algorithms -- 4. Building a Best Choice Recommendation -- 5. How to Create a New Multiple-Criteria Performance Tableau -- 6. Generating Random Performance Tableaux -- 7. Who Wins the Election? -- 8. Ranking with Multiple Incommensurable Criteria -- 9. Rating by Sorting into Relative Performance Quantiles -- 10. Rating-by-Ranking with Learned Performance Quantile Norms -- 11. HPC Ranking of Big Performance Tableaux -- Part III: Evaluation and Decision Case Studies -- 12. Alice’s Best Choice: A Selection Case Study -- 13. The Best Academic Computer Science Depts: A Ranking Case Study -- 14. The Best Students, Where Do They Study? A Rating Case Study -- 15. Exercises -- Part IV: Advanced Topics -- 16. On Measuring the Fitness of a Multiple-Criteria Ranking -- 17. On Computing Digraph Kernels -- 18. On Confident Outrankings with Uncertain Criteria Significance Weights -- 19. Robustness Analysis of Outranking Digraphs -- 20. Tempering Plurality Tyranny Effects in Social Choice -- Part V: Working with Undirected Graphs -- 21. Bipolar-Valued Undirected Graphs -- 22. On Tree Graphs and Graph Forests -- 23. About Split, Comparability, Interval, and Permutation Graphs.
Record Nr. UNINA-9910558496703321
Bisdorff Raymond  
Cham : , : Springer International Publishing : , : Imprint : Springer, , 2022
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