LEADER 08247nam 22006255 450 001 9910370256203321 005 20201022132212.0 010 $a3-030-37599-4 024 7 $a10.1007/978-3-030-37599-7 035 $a(CKB)4900000000505152 035 $a(DE-He213)978-3-030-37599-7 035 $a(MiAaPQ)EBC6005652 035 $a(PPN)242844847 035 $a(EXLCZ)994900000000505152 100 $a20200103d2019 u| 0 101 0 $aeng 135 $aurnn|008mamaa 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aMachine Learning, Optimization, and Data Science $e5th International Conference, LOD 2019, Siena, Italy, September 10?13, 2019, Proceedings /$fedited by Giuseppe Nicosia, Panos Pardalos, Renato Umeton, Giovanni Giuffrida, Vincenzo Sciacca 205 $a1st ed. 2019. 210 1$aCham :$cSpringer International Publishing :$cImprint: Springer,$d2019. 215 $a1 online resource (XXVI, 772 p. 225 illus., 160 illus. in color.) 225 1 $aInformation Systems and Applications, incl. Internet/Web, and HCI ;$v11943 311 $a3-030-37598-6 327 $aDeep 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. 330 $aThis book constitutes the post-conference proceedings of the 5th International Conference on Machine Learning, Optimization, and Data Science, LOD 2019, held in Siena, Italy, in September 2019. The 54 full papers presented were carefully reviewed and selected from 158 submissions. The papers cover topics in the field of machine learning, artificial intelligence, reinforcement learning, computational optimization and data science presenting a substantial array of ideas, technologies, algorithms, methods and applications. 410 0$aInformation Systems and Applications, incl. Internet/Web, and HCI ;$v11943 606 $aApplication software 606 $aArtificial intelligence 606 $aData mining 606 $aInformation Systems Applications (incl. Internet)$3https://scigraph.springernature.com/ontologies/product-market-codes/I18040 606 $aArtificial Intelligence$3https://scigraph.springernature.com/ontologies/product-market-codes/I21000 606 $aData Mining and Knowledge Discovery$3https://scigraph.springernature.com/ontologies/product-market-codes/I18030 615 0$aApplication software. 615 0$aArtificial intelligence. 615 0$aData mining. 615 14$aInformation Systems Applications (incl. Internet). 615 24$aArtificial Intelligence. 615 24$aData Mining and Knowledge Discovery. 676 $a005.14 676 $a006.31 702 $aNicosia$b Giuseppe$4edt$4http://id.loc.gov/vocabulary/relators/edt 702 $aPardalos$b Panos$4edt$4http://id.loc.gov/vocabulary/relators/edt 702 $aUmeton$b Renato$4edt$4http://id.loc.gov/vocabulary/relators/edt 702 $aGiuffrida$b Giovanni$4edt$4http://id.loc.gov/vocabulary/relators/edt 702 $aSciacca$b Vincenzo$4edt$4http://id.loc.gov/vocabulary/relators/edt 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910370256203321 996 $aMachine learning, optimization, and data science$91949690 997 $aUNINA