Название: Machine Learning, Optimization, and Data Science: 4th International Conference, LOD 2018, Volterra, Italy, September 13-16, 2018, Revised Selected Papers Автор: Giuseppe Nicosia, Panos Pardalos, Giovanni Giuffrida Издательство: Springer ISBN: 3030137082 Год: 2019 Страниц: 584 Язык: английский Формат: pdf (true) Размер: 34.4 MB
This book constitutes the post-conference proceedings of the 4th International Conference on Machine Learning, Optimization, and Data Science, LOD 2018, held in Volterra, Italy, in September 2018. The 46 full papers presented were carefully reviewed and selected from 126 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.
Contents:
Calibrating the Classifier: Siamese Neural Network Architecture for End-to-End Arousal Recognition from ECG
Simple Learning with a Teacher via Biased Regularized Least Squares
Feature Based Multivariate Data Imputation
Optimization of Neural Network Training with ELM Based on the Iterative Hybridization of Differential Evolution with Local Search and Restarts
Information-Theoretic Feature Selection Using High-Order Interactions
Covering Arrays to Support the Process of Feature Selection in the Random Forest Classifier
A New Distributed and Decentralized Stochastic Optimization Algorithm with Applications in Big Data Analytics
Generating Term Weighting Schemes Through Genetic Programming
Data-Driven Interactive Multiobjective Optimization Using a Cluster-Based Surrogate in a Discrete Decision Space
Data Science in the Business Environment: Skills Analytics for Curriculum Development
Adaptive Dimensionality Reduction in Multiobjective Optimization with Multiextremal Criteria
REFINE: Representation Learning from Diffusion Events
Augmented Design-Space Exploration by Nonlinear Dimensionality Reduction Methods
Classification and Survival Prediction in Diffuse Large B-Cell Lymphoma by Gene Expression Profiling
Learning Consistent Tree-Augmented Dynamic Bayesian Networks
Designing Ships Using Constrained Multi-objective Efficient Global Optimization
A New Approach to Measuring Distances in Dense Graphs
Ant Colony Optimization for Markov Blanket-Based Feature Selection. Application for Precision Medicine
Average Performance Analysis of the Stochastic Gradient Method for Online PCA
Improving Traditional Dual Ascent Algorithm for the Uncapacitated Multiple Allocation Hub Location Problem: A RAMP Approach
Supervised Learning Approach for Surface-Mount Device Production
Crawling in Rogue’s Dungeons with (Partitioned) A3C
Decision of Neural Networks Hyperparameters with a Population-Based Algorithm
Strong Duality of the Kantorovich-Rubinstein Mass Transshipment Problem in Metric Spaces
Evolutionary Construction of Convolutional Neural Networks - Pages 293-304 ...
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