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Machine Learning, Optimization, and Data Science

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Cover of 'Machine Learning, Optimization, and Data Science'

Table of Contents

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    Book Overview
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    Chapter 1 Calibrating the Classifier: Siamese Neural Network Architecture for End-to-End Arousal Recognition from ECG
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    Chapter 2 Simple Learning with a Teacher via Biased Regularized Least Squares
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    Chapter 3 Feature Based Multivariate Data Imputation
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    Chapter 4 Optimization of Neural Network Training with ELM Based on the Iterative Hybridization of Differential Evolution with Local Search and Restarts
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    Chapter 5 Information-Theoretic Feature Selection Using High-Order Interactions
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    Chapter 6 Covering Arrays to Support the Process of Feature Selection in the Random Forest Classifier
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    Chapter 7 A New Distributed and Decentralized Stochastic Optimization Algorithm with Applications in Big Data Analytics
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    Chapter 8 Generating Term Weighting Schemes Through Genetic Programming
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    Chapter 9 Data-Driven Interactive Multiobjective Optimization Using a Cluster-Based Surrogate in a Discrete Decision Space
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    Chapter 10 Data Science in the Business Environment: Skills Analytics for Curriculum Development
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    Chapter 11 Adaptive Dimensionality Reduction in Multiobjective Optimization with Multiextremal Criteria
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    Chapter 12 REFINE: Representation Learning from Diffusion Events
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    Chapter 13 Augmented Design-Space Exploration by Nonlinear Dimensionality Reduction Methods
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    Chapter 14 Classification and Survival Prediction in Diffuse Large B-Cell Lymphoma by Gene Expression Profiling
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    Chapter 15 Learning Consistent Tree-Augmented Dynamic Bayesian Networks
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    Chapter 16 Designing Ships Using Constrained Multi-objective Efficient Global Optimization
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    Chapter 17 A New Approach to Measuring Distances in Dense Graphs
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    Chapter 18 Ant Colony Optimization for Markov Blanket-Based Feature Selection. Application for Precision Medicine
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    Chapter 19 Average Performance Analysis of the Stochastic Gradient Method for Online PCA
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    Chapter 21 Supervised Learning Approach for Surface-Mount Device Production
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    Chapter 22 Crawling in Rogue’s Dungeons with (Partitioned) A3C
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    Chapter 23 Decision of Neural Networks Hyperparameters with a Population-Based Algorithm
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    Chapter 24 Strong Duality of the Kantorovich-Rubinstein Mass Transshipment Problem in Metric Spaces
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    Chapter 25 Evolutionary Construction of Convolutional Neural Networks
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    Chapter 26 Improving Clinical Subjects Clustering by Learning and Optimizing Feature Weights
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    Chapter 27 A Framework to Automatically Extract Funding Information from Text
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    Chapter 28 Speeding Up Budgeted Stochastic Gradient Descent SVM Training with Precomputed Golden Section Search
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    Chapter 29 An Unsupervised Learning Classifier with Competitive Error Performance
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    Chapter 30 A GRASP/VND Heuristic for the Max Cut-Clique Problem
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    Chapter 31 A Modelica-Based Simulation Method for Black-Box Optimal Control Problems with Level-Set Dynamic Programming
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    Chapter 32 A Clonal Selection Algorithm for Multiobjective Energy Reduction Multi-Depot Vehicle Routing Problem
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    Chapter 33 Big Data Privacy by Design Computation Platform
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    Chapter 34 Assessing Accuracy of Ensemble Learning for Facial Expression Recognition with CNNs
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    Chapter 35 Processing Online SAT Instances with Waiting Time Constraints and Completion Weights
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    Chapter 36 Variable Selection and Outlier Detection in Regularized Survival Models: Application to Melanoma Gene Expression Data
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    Chapter 37 Methods of Machine Learning for Censored Demand Prediction
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    Chapter 38 N-Gram Representation for Web Service Description Classification
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    Chapter 39 Lookahead Policy and Genetic Algorithm for Solving Nurse Rostering Problems
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    Chapter 40 Image-Based Fashion Product Recommendation with Deep Learning
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    Chapter 41 A Machine Learning Approach for Line Outage Identification in Power Systems
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    Chapter 42 Sparse Feature Extraction Model with Independent Subspace Analysis
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    Chapter 43 Bayesian Clustering of Multivariate Immunological Data
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    Chapter 44 Nonnegative Coupled Matrix Tensor Factorization for Smart City Spatiotemporal Pattern Mining
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    Chapter 45 User Preferences in Bayesian Multi-objective Optimization: The Expected Weighted Hypervolume Improvement Criterion
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    Chapter 46 Reinforcement Learning Methods for Operations Research Applications: The Order Release Problem
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Title
Machine Learning, Optimization, and Data Science
Published by
Springer International Publishing, April 2019
DOI 10.1007/978-3-030-13709-0
ISBNs
978-3-03-013708-3, 978-3-03-013709-0
Editors

Nicosia, Giuseppe, Pardalos, Panos, Giuffrida, Giovanni, Umeton, Renato, Sciacca, Vincenzo

Twitter Demographics

The data shown below were collected from the profiles of 6 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 4 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 4 100%

Demographic breakdown

Readers by professional status Count As %
Unspecified 2 50%
Lecturer 1 25%
Student > Master 1 25%
Readers by discipline Count As %
Unspecified 2 50%
Business, Management and Accounting 1 25%
Computer Science 1 25%