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Machine Learning, Optimization, and Data Science [[electronic resource] ] : 4th International Conference, LOD 2018, Volterra, Italy, September 13-16, 2018, Revised Selected Papers / / edited by Giuseppe Nicosia, Panos Pardalos, Giovanni Giuffrida, Renato Umeton, Vincenzo Sciacca
| Machine Learning, Optimization, and Data Science [[electronic resource] ] : 4th International Conference, LOD 2018, Volterra, Italy, September 13-16, 2018, Revised Selected Papers / / edited by Giuseppe Nicosia, Panos Pardalos, Giovanni Giuffrida, Renato Umeton, Vincenzo Sciacca |
| Edizione | [1st ed. 2019.] |
| Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2019 |
| Descrizione fisica | 1 online resource (XXII, 562 p. 224 illus., 115 illus. in color.) |
| Disciplina | 006.31 |
| Collana | Information Systems and Applications, incl. Internet/Web, and HCI |
| Soggetto topico |
Application software
Machine learning Algorithms Data mining Information Systems Applications (incl. Internet) Machine Learning Algorithm Analysis and Problem Complexity Data Mining and Knowledge Discovery |
| ISBN | 3-030-13709-0 |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Machine learning -- Artificial intelligence -- Reinforcement learning -- Computational optimization -- Data science presenting -- Deep learning -- Big data -- Data analytics -- Neural networks. |
| Record Nr. | UNISA-996466425003316 |
| Cham : , : Springer International Publishing : , : Imprint : Springer, , 2019 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. di Salerno | ||
| ||
Machine Learning, Optimization, and Data Science [[electronic resource] ] : 5th International Conference, LOD 2019, Siena, Italy, September 10–13, 2019, Proceedings / / edited by Giuseppe Nicosia, Panos Pardalos, Renato Umeton, Giovanni Giuffrida, Vincenzo Sciacca
| Machine Learning, Optimization, and Data Science [[electronic resource] ] : 5th International Conference, LOD 2019, Siena, Italy, September 10–13, 2019, Proceedings / / edited by Giuseppe Nicosia, Panos Pardalos, Renato Umeton, Giovanni Giuffrida, Vincenzo Sciacca |
| Edizione | [1st ed. 2019.] |
| Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2019 |
| Descrizione fisica | 1 online resource (XXVI, 772 p. 225 illus., 160 illus. in color.) |
| Disciplina | 005.14 |
| Collana | Information Systems and Applications, incl. Internet/Web, and HCI |
| Soggetto topico |
Application software
Artificial intelligence Data mining Information Systems Applications (incl. Internet) Artificial Intelligence Data Mining and Knowledge Discovery |
| ISBN | 3-030-37599-4 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Deep Neural Network Ensembles -- Driver Distraction Detection Using Deep Neural Network -- Deep Learning Algorithms for Complex Pattern Recognition in Ultrasonic Sensors Arrays -- An Information Analysis Approach into Feature Understanding of Convolutional Deep Neural Networks -- Stochastic Weight Matrix-based Regularization Methods for Deep Neural Networks -- Quantitative and Ontology-Based Comparison of Explanations for Image Classification -- About generative aspects of Variational Autoencoders -- Adapted Random Survival Forest for Histograms to Analyze NOx Sensor Failure in Heavy Trucks -- Incoherent submatrix selection via approximate independence sets in scalar product graphs -- LIA: A Label-Independent Algorithm for Feature Selection for Supervised Learning -- Relationship Estimation Metrics for Binary SoC Data -- Network Alignment using Graphlet Signature and High Order Proximity -- Effect of Market Spread over Reinforcement Learning based Market Maker -- A Beam Search for the Longest Common Subsequence Problem Guided by a Novel Approximate Expected Length Calculation -- An Adaptive Parameter Free Particle Swarm Optimization Algorithm for the Permutation Flowshop Scheduling Problem -- The measure of regular relations recognition applied to the supervised classification task -- Simple and Accurate classifi cation method based on Class Association Rules performs well on well-known datasets -- Analyses of Multi-collection Corpora via Compound Topic Modeling -- Text mining with constrained tensor decomposition -- The induction problem: a machine learning vindication argument -- Geospatial Dimension in Association Rule Mining: The Case Study of the Amazon Charcoal Tree -- On Probabilistic k-Richness of the k-Means Algorithms -- Using clustering for supervised feature selection to detect relevant features -- A Structural Theorem for Center-Based Clustering in High-Dimensional Euclidean Space -- Modification of the k-MXT Algorithm and Its Application to the Geotagged Data Clustering -- CoPASample: A Heuristics based Covariance Preserving Data Augmentation -- Active Matrix Completion for Algorithm Selection -- A Framework for Multi- delity Modeling in Global Optimization Approaches -- Performance Evaluation of Local Surrogate Models in Bilevel Optimization -- BowTie - a deep learning feedforward neural network for sentiment analysis -- To What Extent Can Text Classifiation Help with Making Inferences About Students' Understanding -- Combinatorial Learning in Traffic Management -- Cartesian Genetic Programming with Guided and Single Active Mutations for Designing Combinational Logic Circuits -- Designing an Optimal and Resilient iBGP Overlay with extended ORRTD -- GRASP Heuristics for the Stochastic Weighted Graph Fragmentation Problem -- Uniformly Most-Reliable Graphs and Antiholes -- Merging Quality Estimation for Binary Decision Diagrams with Binary Classfi ers -- Directed Acyclic Graph Reconstruction Leveraging Prior Partial Ordering Information -- Learning Scale and Shift-Invariant Dictionary for Sparse Representation -- Robust kernelized Bayesian matrix factorization for video background/foreground separation -- Parameter Optimization of Polynomial Kernel SVM from miniCV -- Analysing the Over t of the auto-sklearn Automated Machine Learning Tool -- A New Baseline for Automated Hyper-Parameter Optimization -- Optimal trade-o between sample size and precision of supervision for the xed effects panel data model -- Restaurant Health Inspections and Crime Statistics Predict the Real Estate Market in New York City -- Load Forecasting in District Heating Networks: Model Comparison on a Real-World Case Study -- A Chained Neural Network Model for Photovoltaic Power Forecast -- Trading-o Data Fit and Complexity in Training Gaussian Processes with Multiple Kernels -- Designing Combinational Circuits Using a Multi-objective Cartesian Genetic Programming with Adaptive Population Size -- Multi-Task Learning by Pareto Optimality Nicosia -- Vital prognosis of patients in intensive care units using an Ensemble of Bayesian Classifiers -- On the role of hub and orphan genes in the diagnosis of breast invasive carcinoma -- Approximating Probabilistic Constraints for Surgery Scheduling using Neural Networks -- Determining Principal Component Cardinality through the Principle of Minimum Description Length -- Modelling chaotic time series using recursive deep self-organising neural networks -- On Tree-based Methods for Similarity Learning -- Active Learning Approach for Safe Process Parameter Tuning -- Federated Learning of Deep Neural Decision Forests -- Data Anonymization for Privacy aware Machine Learning -- Exploiting Similar Behavior of Users in a Cooperative Optimization Approach for Distributing Service Points in Mobility Applications -- Long Short-Term Memory Networks for Earthquake Detection in Venezuelan Regions -- Zero-Shot Fashion Products Clustering on Social Image Streams -- Treating Arti cial Neural Net Training as a Nonsmooth Global Optimization Problem. |
| Record Nr. | UNISA-996466225003316 |
| Cham : , : Springer International Publishing : , : Imprint : Springer, , 2019 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. di Salerno | ||
| ||
Machine Learning, Optimization, and Data Science : 5th International Conference, LOD 2019, Siena, Italy, September 10–13, 2019, Proceedings / / edited by Giuseppe Nicosia, Panos Pardalos, Renato Umeton, Giovanni Giuffrida, Vincenzo Sciacca
| Machine Learning, Optimization, and Data Science : 5th International Conference, LOD 2019, Siena, Italy, September 10–13, 2019, Proceedings / / edited by Giuseppe Nicosia, Panos Pardalos, Renato Umeton, Giovanni Giuffrida, Vincenzo Sciacca |
| Edizione | [1st ed. 2019.] |
| Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2019 |
| Descrizione fisica | 1 online resource (XXVI, 772 p. 225 illus., 160 illus. in color.) |
| Disciplina |
005.14
006.31 |
| Collana | Information Systems and Applications, incl. Internet/Web, and HCI |
| Soggetto topico |
Application software
Artificial intelligence Data mining Information Systems Applications (incl. Internet) Artificial Intelligence Data Mining and Knowledge Discovery |
| ISBN | 3-030-37599-4 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Deep Neural Network Ensembles -- Driver Distraction Detection Using Deep Neural Network -- Deep Learning Algorithms for Complex Pattern Recognition in Ultrasonic Sensors Arrays -- An Information Analysis Approach into Feature Understanding of Convolutional Deep Neural Networks -- Stochastic Weight Matrix-based Regularization Methods for Deep Neural Networks -- Quantitative and Ontology-Based Comparison of Explanations for Image Classification -- About generative aspects of Variational Autoencoders -- Adapted Random Survival Forest for Histograms to Analyze NOx Sensor Failure in Heavy Trucks -- Incoherent submatrix selection via approximate independence sets in scalar product graphs -- LIA: A Label-Independent Algorithm for Feature Selection for Supervised Learning -- Relationship Estimation Metrics for Binary SoC Data -- Network Alignment using Graphlet Signature and High Order Proximity -- Effect of Market Spread over Reinforcement Learning based Market Maker -- A Beam Search for the Longest Common Subsequence Problem Guided by a Novel Approximate Expected Length Calculation -- An Adaptive Parameter Free Particle Swarm Optimization Algorithm for the Permutation Flowshop Scheduling Problem -- The measure of regular relations recognition applied to the supervised classification task -- Simple and Accurate classifi cation method based on Class Association Rules performs well on well-known datasets -- Analyses of Multi-collection Corpora via Compound Topic Modeling -- Text mining with constrained tensor decomposition -- The induction problem: a machine learning vindication argument -- Geospatial Dimension in Association Rule Mining: The Case Study of the Amazon Charcoal Tree -- On Probabilistic k-Richness of the k-Means Algorithms -- Using clustering for supervised feature selection to detect relevant features -- A Structural Theorem for Center-Based Clustering in High-Dimensional Euclidean Space -- Modification of the k-MXT Algorithm and Its Application to the Geotagged Data Clustering -- CoPASample: A Heuristics based Covariance Preserving Data Augmentation -- Active Matrix Completion for Algorithm Selection -- A Framework for Multi- delity Modeling in Global Optimization Approaches -- Performance Evaluation of Local Surrogate Models in Bilevel Optimization -- BowTie - a deep learning feedforward neural network for sentiment analysis -- To What Extent Can Text Classifiation Help with Making Inferences About Students' Understanding -- Combinatorial Learning in Traffic Management -- Cartesian Genetic Programming with Guided and Single Active Mutations for Designing Combinational Logic Circuits -- Designing an Optimal and Resilient iBGP Overlay with extended ORRTD -- GRASP Heuristics for the Stochastic Weighted Graph Fragmentation Problem -- Uniformly Most-Reliable Graphs and Antiholes -- Merging Quality Estimation for Binary Decision Diagrams with Binary Classfi ers -- Directed Acyclic Graph Reconstruction Leveraging Prior Partial Ordering Information -- Learning Scale and Shift-Invariant Dictionary for Sparse Representation -- Robust kernelized Bayesian matrix factorization for video background/foreground separation -- Parameter Optimization of Polynomial Kernel SVM from miniCV -- Analysing the Over t of the auto-sklearn Automated Machine Learning Tool -- A New Baseline for Automated Hyper-Parameter Optimization -- Optimal trade-o between sample size and precision of supervision for the xed effects panel data model -- Restaurant Health Inspections and Crime Statistics Predict the Real Estate Market in New York City -- Load Forecasting in District Heating Networks: Model Comparison on a Real-World Case Study -- A Chained Neural Network Model for Photovoltaic Power Forecast -- Trading-o Data Fit and Complexity in Training Gaussian Processes with Multiple Kernels -- Designing Combinational Circuits Using a Multi-objective Cartesian Genetic Programming with Adaptive Population Size -- Multi-Task Learning by Pareto Optimality Nicosia -- Vital prognosis of patients in intensive care units using an Ensemble of Bayesian Classifiers -- On the role of hub and orphan genes in the diagnosis of breast invasive carcinoma -- Approximating Probabilistic Constraints for Surgery Scheduling using Neural Networks -- Determining Principal Component Cardinality through the Principle of Minimum Description Length -- Modelling chaotic time series using recursive deep self-organising neural networks -- On Tree-based Methods for Similarity Learning -- Active Learning Approach for Safe Process Parameter Tuning -- Federated Learning of Deep Neural Decision Forests -- Data Anonymization for Privacy aware Machine Learning -- Exploiting Similar Behavior of Users in a Cooperative Optimization Approach for Distributing Service Points in Mobility Applications -- Long Short-Term Memory Networks for Earthquake Detection in Venezuelan Regions -- Zero-Shot Fashion Products Clustering on Social Image Streams -- Treating Arti cial Neural Net Training as a Nonsmooth Global Optimization Problem. |
| Record Nr. | UNINA-9910370256203321 |
| Cham : , : Springer International Publishing : , : Imprint : Springer, , 2019 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Machine Learning, Optimization, and Data Science : 4th International Conference, LOD 2018, Volterra, Italy, September 13-16, 2018, Revised Selected Papers / / edited by Giuseppe Nicosia, Panos Pardalos, Giovanni Giuffrida, Renato Umeton, Vincenzo Sciacca
| Machine Learning, Optimization, and Data Science : 4th International Conference, LOD 2018, Volterra, Italy, September 13-16, 2018, Revised Selected Papers / / edited by Giuseppe Nicosia, Panos Pardalos, Giovanni Giuffrida, Renato Umeton, Vincenzo Sciacca |
| Edizione | [1st ed. 2019.] |
| Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2019 |
| Descrizione fisica | 1 online resource (XXII, 562 p. 224 illus., 115 illus. in color.) |
| Disciplina | 006.31 |
| Collana | Information Systems and Applications, incl. Internet/Web, and HCI |
| Soggetto topico |
Application software
Machine learning Algorithms Data mining Information Systems Applications (incl. Internet) Machine Learning Algorithm Analysis and Problem Complexity Data Mining and Knowledge Discovery |
| ISBN | 3-030-13709-0 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Machine learning -- Artificial intelligence -- Reinforcement learning -- Computational optimization -- Data science presenting -- Deep learning -- Big data -- Data analytics -- Neural networks. |
| Record Nr. | UNINA-9910337583303321 |
| Cham : , : Springer International Publishing : , : Imprint : Springer, , 2019 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||