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ORCID16th PPSN 2020: Leiden, The Netherlands - Part I
- Thomas Bäck
, Mike Preuss, André H. Deutz, Hao Wang, Carola Doerr, Michael T. M. Emmerich, Heike Trautmann:
Parallel Problem Solving from Nature - PPSN XVI - 16th International Conference, PPSN 2020, Leiden, The Netherlands, September 5-9, 2020, Proceedings, Part I. Lecture Notes in Computer Science 12269, Springer 2020, ISBN 978-3-030-58111-4
Automated Algorithm Selection and Configuration
- Ying Bi, Bing Xue, Mengjie Zhang:
Evolving Deep Forest with Automatic Feature Extraction for Image Classification Using Genetic Programming. 3-18 - George T. Hall, Pietro S. Oliveto, Dirk Sudholt:
Fast Perturbative Algorithm Configurators. 19-32 - Arnaud Liefooghe, Sébastien Vérel, Bilel Derbel, Hernán E. Aguirre, Kiyoshi Tanaka:
Dominance, Indicator and Decomposition Based Search for Multi-objective QAP: Landscape Analysis and Automated Algorithm Selection. 33-47 - Moritz Seiler, Janina Pohl, Jakob Bossek, Pascal Kerschke, Heike Trautmann:
Deep Learning as a Competitive Feature-Free Approach for Automated Algorithm Selection on the Traveling Salesperson Problem. 48-64 - Sara Tari, Holger H. Hoos, Julie Jacques, Marie-Eléonore Kessaci, Laetitia Jourdan:
Automatic Configuration of a Multi-objective Local Search for Imbalanced Classification. 65-77
Bayesian- and Surrogate-Assisted Optimization
- Youhei Akimoto, Naoki Sakamoto, Makoto Ohtani:
Multi-fidelity Optimization Approach Under Prior and Posterior Constraints and Its Application to Compliance Minimization. 81-94 - Marie Anastacio, Holger H. Hoos:
Model-Based Algorithm Configuration with Default-Guided Probabilistic Sampling. 95-110 - Jakob Bossek, Carola Doerr, Pascal Kerschke, Aneta Neumann, Frank Neumann:
Evolving Sampling Strategies for One-Shot Optimization Tasks. 111-124 - Guoxia Fu, Chaoli Sun, Ying Tan, Guochen Zhang, Yaochu Jin:
A Surrogate-Assisted Evolutionary Algorithm with Random Feature Selection for Large-Scale Expensive Problems. 125-139 - Alexander Hagg, Dominik Wilde, Alexander Asteroth, Thomas Bäck:
Designing Air Flow with Surrogate-Assisted Phenotypic Niching. 140-153 - Laurent Meunier, Carola Doerr, Jérémy Rapin, Olivier Teytaud:
Variance Reduction for Better Sampling in Continuous Domains. 154-168 - Elena Raponi, Hao Wang, Mariusz Bujny, Simonetta Boria, Carola Doerr:
High Dimensional Bayesian Optimization Assisted by Principal Component Analysis. 169-183 - Lauchlan Toal, Dirk V. Arnold:
Simple Surrogate Model Assisted Optimization with Covariance Matrix Adaptation. 184-197
Benchmarking and Performance Measures
- Weiyu Chen, Hisao Ishibuchi, Ke Shang:
Proposal of a Realistic Many-Objective Test Suite. 201-214 - Andrzej Jaszkiewicz, Robert Susmaga, Piotr Zielniewicz:
Approximate Hypervolume Calculation with Guaranteed or Confidence Bounds. 215-228 - Anna V. Kononova, Fabio Caraffini, Hao Wang, Thomas Bäck:
Can Compact Optimisation Algorithms Be Structurally Biased? 229-242 - Margarita Alejandra Rebolledo Coy, Frederik Rehbach, A. E. Eiben, Thomas Bartz-Beielstein:
Parallelized Bayesian Optimization for Expensive Robot Controller Evolution. 243-256 - Ryoji Tanabe:
Revisiting Population Models in Differential Evolution on a Limited Budget of Evaluations. 257-272 - Martin Zaefferer, Frederik Rehbach:
Continuous Optimization Benchmarks by Simulation. 273-286 - Alexandru-Ciprian Zavoianu, Benjamin Lacroix, John McCall:
Comparative Run-Time Performance of Evolutionary Algorithms on Multi-objective Interpolated Continuous Optimisation Problems. 287-300
Combinatorial Optimization
- Omar Abdelkafi, Bilel Derbel, Arnaud Liefooghe, Darrell Whitley:
On the Design of a Partition Crossover for the Quadratic Assignment Problem. 303-316 - Mohammad Bagherbeik, Parastoo Ashtari, Seyed Farzad Mousavi, Kouichi Kanda, Hirotaka Tamura, Ali Sheikholeslami:
A Permutational Boltzmann Machine with Parallel Tempering for Solving Combinatorial Optimization Problems. 317-331 - Léa Blaise, Christian Artigues, Thierry Benoist:
Solution Repair by Inequality Network Propagation in LocalSolver. 332-345 - Jakob Bossek, Aneta Neumann, Frank Neumann:
Optimising Tours for the Weighted Traveling Salesperson Problem and the Traveling Thief Problem: A Structural Comparison of Solutions. 346-359 - Lee A. Christie:
Decentralized Combinatorial Optimization. 360-372 - Chuan Luo, Holger H. Hoos, Shaowei Cai:
PbO-CCSAT: Boosting Local Search for Satisfiability Using Programming by Optimisation. 373-389 - Lily Major, Amanda Clare, Jacqueline W. Daykin, Benjamin Mora, Leonel Jose Peña Gamboa, Christine Zarges:
Evaluation of a Permutation-Based Evolutionary Framework for Lyndon Factorizations. 390-403 - Aneta Neumann, Frank Neumann:
Optimising Monotone Chance-Constrained Submodular Functions Using Evolutionary Multi-objective Algorithms. 404-417 - Szymon Wozniak, Michal Przewozniczek, Marcin M. Komarnicki:
Parameter-Less Population Pyramid for Permutation-Based Problems. 418-430
Connection Between Nature-Inspired Optimization and Artificial Intelligence
- Marcin Bialas, Marcin Michal Mironczuk, Jacek Mandziuk:
Biologically Plausible Learning of Text Representation with Spiking Neural Networks. 433-447 - Susanne Dandl, Christoph Molnar, Martin Binder, Bernd Bischl:
Multi-Objective Counterfactual Explanations. 448-469 - Wenjing Hong, Peng Yang, Yiwen Wang, Ke Tang:
Multi-objective Magnitude-Based Pruning for Latency-Aware Deep Neural Network Compression. 470-483 - Shengxiang Hu, Bofeng Zhang, Ying Lv, Furong Chang, Zhuocheng Zhou:
Network Representation Learning Based on Topological Structure and Vertex Attributes. 484-497 - Stanislaw Kazmierczak, Jacek Mandziuk:
A Committee of Convolutional Neural Networks for Image Classification in the Concurrent Presence of Feature and Label Noise. 498-511 - Jiawen Kong, Wojtek Kowalczyk, Stefan Menzel, Thomas Bäck:
Improving Imbalanced Classification by Anomaly Detection. 512-523 - Romain Orhand, Anne Jeannin-Girardon, Pierre Parrend, Pierre Collet:
BACS: A Thorough Study of Using Behavioral Sequences in ACS2. 524-538 - Mihai-Alexandru Suciu, Rodica Ioana Lung:
Nash Equilibrium as a Solution in Supervised Classification. 539-551 - Jamal Toutouh, Erik Hemberg, Una-May O'Reilly:
Analyzing the Components of Distributed Coevolutionary GAN Training. 552-566 - Wenjing Wang, Yuwu Lu, Zhihui Lai:
Canonical Correlation Discriminative Learning for Domain Adaptation. 567-580
Genetic and Evolutionary Algorithms
- Stephen Friess, Peter Tiño, Stefan Menzel, Bernhard Sendhoff, Xin Yao:
Improving Sampling in Evolution Strategies Through Mixture-Based Distributions Built from Past Problem Instances. 583-596 - Tobias Glasmachers, Oswin Krause:
The Hessian Estimation Evolution Strategy. 597-609 - Johannes Lengler, Jonas Meier:
Large Population Sizes and Crossover Help in Dynamic Environments. 610-622 - Pawel Liskowski, Krzysztof Krawiec, Nihat Engin Toklu:
Neuromemetic Evolutionary Optimization. 623-636 - Nicola Mc Donnell, Enda Howley, Jim Duggan:
Evolved Gossip Contracts - A Framework for Designing Multi-agent Systems. 637-649 - Oscar Pacheco-Del-Moral, Carlos A. Coello Coello:
A SHADE-Based Algorithm for Large Scale Global Optimization. 650-663 - Amirhossein Rajabi, Carsten Witt:
Evolutionary Algorithms with Self-adjusting Asymmetric Mutation. 664-677 - Franciszek Seredynski, Jakub Gasior:
Behavior Optimization in Large Distributed Systems Modeled by Cellular Automata. 678-690 - Gresa Shala, André Biedenkapp, Noor H. Awad, Steven Adriaensen, Marius Lindauer, Frank Hutter:
Learning Step-Size Adaptation in CMA-ES. 691-706 - Konstantinos Varelas, Anne Auger, Nikolaus Hansen:
Sparse Inverse Covariance Learning for CMA-ES with Graphical Lasso. 707-718 - Teppei Yamaguchi, Kento Uchida, Shinichi Shirakawa:
Adaptive Stochastic Natural Gradient Method for Optimizing Functions with Low Effective Dimensionality. 719-731
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