Learning and Intelligent Optimization
Springer International Publishing (Verlag)
978-3-031-24865-8 (ISBN)
The 36 full papers and 3 short papers presented in this volume were carefully reviewed and selected from 60 submissions. LION deals with automatic solver configuration, parallel methods, intelligent optimization, nature-inspired algorithms, hard combinatorial optimization problems, DC learning, computational intelligence, and others. The contributions were organized in topical sections as follows: Invited Papers; Contributed Papers.
Invited Papers.- Optimal Scheduling of the Leaves of a Tree and the SVO Frequencies of Languages.- From Design of Experiments to Combinatorics of Disasters: A Conceptual Framework for Disaster Exercises.- Separating two polyhedra utilizing alternative theorems and penalty function.- Contributed Papers. -A Composite Index Method for Optimization Benchmarking.- Optimal Energy Management of Microgrid Using Multi-objective Optimisation Approach.- A Stochastic Alternating Balance k-Means Algorithm for Fair Clustering.- Binary Black Widow Optimization Algorithm for Feature Selection Problems.- Learning to Solve a Stochastic Orienteering Problem with Time Windows.- ML-based approach for accelerating global search algorithm for solving multicriteria problems .- The Skewed Kruskal algorithm.- Bounds for sparse solutions of K-SVCR multi-class classification model.- Integer Linear Programming in Solving an Optimization Problem at the Mixing Department of the Metallurgical Production.- Realtime Gray-Box Algorithm Configuration.- Dynamic urban solid waste management system for smart cities.- Single MCMC Chain Parallelisation on Decision Trees.- Single MCMC Chain Parallelisation on Decision Trees.- Competitive supply allocation in a distribution network under overproduction.- Safe-exploration of control policies from safe-experience via Gaussian Processes.- Bayesian Optimization in Wasserstein Spaces.- Network Vulnerability Analysis in Wasserstein Spaces.- BERT Self-Learning Approach with Limited Labels for Document Classification.- Autonomous Learning Optimization for Deep Learning.- Optimizing Data Augmentation Policy through Random Unidimensional Search.- Evaluating Student Behaviour on the MathE Platform - Clustering Algorithms Approaches.- Unsupervised Training for Neural TSP Solver.- Comparing surrogate models for tuning optimization algorithms.- Search and Score-based Waterfall Auction Optimization.- Survey on KNN Methods in Data Science.- Constrained Shortest Path and Hierarchical Structures.- Investigation of Graph Neural Networks for Instance Segmentation of Industrial Point Cloud Data.- Fitness landscape ruggedness impact on PSO in dealing with three variants of the travelling salesman problem.- A Multi-UAVs' Provider Model for the provision of 5G Service Chains: a game theoretic approach.- Metabolic Syndrome Risk Forecasting on Elderly with ML Techniques.- Airport Digital Twins for Resilient Disaster Management Response.- Strategies for Surviving Aggressive Multiparty Repeated Standoffs.- A Hybridization of GRASP and UTASTAR for Solving the Vehicle Routing Problem with Pickups and Deliveries and 3D Loading Constraints.- Packing hypertrees and the k-cut problem in Hypergraphs.- Maximizing the Eigenvalue-Gap and Promoting Sparsity ofDoubly Stochastic Matrices with PSO.- Value of Information in the Mean-Square Case and its Application to the Analysis of Financial Time-Series Forecast.
| Erscheinungsdatum | 07.02.2023 |
|---|---|
| Reihe/Serie | Lecture Notes in Computer Science |
| Zusatzinfo | XIV, 566 p. 171 illus., 140 illus. in color. |
| Verlagsort | Cham |
| Sprache | englisch |
| Maße | 155 x 235 mm |
| Gewicht | 878 g |
| Themenwelt | Mathematik / Informatik ► Informatik ► Netzwerke |
| Informatik ► Theorie / Studium ► Algorithmen | |
| Informatik ► Weitere Themen ► Hardware | |
| Mathematik / Informatik ► Mathematik ► Analysis | |
| Mathematik / Informatik ► Mathematik ► Wahrscheinlichkeit / Kombinatorik | |
| Schlagworte | Artificial Intelligence • clustering algorithms • Computer Hardware • Computer Networks • Computer systems • Correlation Analysis • Data Mining • Education • Engineering • graph theory • Internet • learning • machine learning • Mathematics • Network Protocols • Optimization • Optimization Problems • Probability • Signal Processing • Software engineering |
| ISBN-10 | 3-031-24865-1 / 3031248651 |
| ISBN-13 | 978-3-031-24865-8 / 9783031248658 |
| Zustand | Neuware |
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