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Optimization and Learning: 6th International Conference, OLA 2023, Malaga, Spain, May 3–5, 2023, Proceedings de Bernabé Dorronsoro

Optimization and Learning: 6th International Conference, OLA 2023, Malaga, Spain, May 3–5, 2023, Proceedings: Communications in Computer and Information Science, cartea 1824

Editat de Bernabé Dorronsoro, Francisco Chicano, Gregoire Danoy, El-Ghazali Talbi
en Limba Engleză Paperback – 27 mai 2023
This book constitutes the refereed proceedings of the 6th International Conference on Optimization and Learning, OLA 2023, held in Malaga, Spain, during May 3–5, 2023. 
The 32 full papers included in this book were carefully reviewed and selected from 78 submissions. They were organized in topical sections as follows: advanced optimization; learning; learning methods to enhance optimization tools; optimization applied to learning methods; and real-world applications.

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Specificații

ISBN-13: 9783031340192
ISBN-10: 3031340191
Pagini: 428
Ilustrații: XIV, 428 p. 136 illus., 119 illus. in color.
Dimensiuni: 155 x 235 mm
Greutate: 0.62 kg
Ediția:1st ed. 2023
Editura: Springer Nature Switzerland
Colecția Springer
Seria Communications in Computer and Information Science

Locul publicării:Cham, Switzerland

Cuprins

​Advanced Optimization.- A comparative study of fractal-based decomposition optimization.- Diagonal Barzilai-Borwein rules in stochastic gradient-like methods.- Algorithm Selection for Large-Scale Multi-objective Optimization.- Solving a Multi-Objective Jop Shop Scheduling Problem With An Automatically Configured Evolutionary Algorithm.- Solving the Nurse Scheduling Problem using the Whale Optimization Algorithm.- A hierarchical Cooperative Coevolutionary approach to solve Very Large-scale Traveling Salesman Problem.- Tornado: An Autonomous Chaotic Algorithm For High Dimensional Global Optimization Problems.- Learning.- Neural Network Information Leakage through Hidden Learning.- Mixing Data Augmentation Methods for Semantic Segmentation.- Real-time elastic partial shape matching using a neural network-based adjoint method.- We won’t get fooled again: when performance metric malfunction affects the landscape of hyperparameter optimization problems.- Condition-based maintenance optimization under large action space with deep reinforcement learning method.- Learning methods to enhance optimization tools.- An Application of Machine Learning Tools to Predict the Number of Solutions for a Minimum Cardinality Set Covering Problem.- Adaptative Local Search for a Pickup and Delivery Problem Applied to Large Parcel Distribution.- Graph Reinforcement Learning for Operator Selection in the ALNS Metaheuristic.- Multi-objective optimization of adhesive bonding process in constrained and noisy settings.- Evaluating Surrogate Models for Robot Swarm Simulations.- Interactive Job Scheduling with Partially Known Personnel Availabilities.- Multi-Armed Bandit-based Metaheuristic Operator Selection: The Pendulum Algorithm binarization case.- Optimization applied to learning methods.- BinaryBlack Widow with Hill Climbing Algorithm for Feature Selection.- Optimization of Fuzzy C-Means with Alternating Direction Method of Multipliers.- Partial K-means with M outliers: Mathematical programs and complexity results.- An optimization approach for optimizing PRIM’s randomly generated rules using the Genetic Algorithm.- Real-world Applications.- A fast methodology to find Decisively Strong Association Rules (DSR).- Characterization and categorization of software programs on x86 architectures.- Robot-Assisted Delivery problems and Their Exact Solutions.- Modeling and analysis of organizational network analysis graphs based  on employee data.- Time Series Forecasting for Parking Occupancy: Case Study of Malaga and Birmingham Cities.- E-scooters Routes Potential: Open Data Analysis in Current Infrastructure. Malaga Case.- Automatic Generation of Subtitles for Videos of the Government of La Rioja.- Estimation of the distribution of Body Mass Index (BMI) with sparse and low-quality data. The case of the Chilean adult population.- A New Automated Customer Prioritization Method.