Applications of Evolutionary Computation : 17th European Conference, EvoApplications 2014, Granada, Spain, April 23-25, 2014 : revised selected papers. EvoApplications (Conference) (17th : 2014 : Granada, Spain)最新文献

Applications of Evolutionary Computation: 26th European Conference, EvoApplications 2023, Held as Part of EvoStar 2023, Brno, Czech Republic, April 12–14, 2023, Proceedings 进化计算的应用:第26届欧洲会议，EvoApplications 2023，作为EvoStar 2023的一部分，Brno，捷克共和国，4月12-14日，2023,Proceedings

Applications of Evolutionary Computation : 17th European Conference, EvoApplications 2014, Granada, Spain, April 23-25, 2014 : revised selected papers. EvoApplications (Conference) (17th : 2014 : Granada, Spain) Pub Date : 2023-01-01 DOI: 10.1007/978-3-031-30229-9

引用次数: 0

Optimising Communication Overhead in Federated Learning Using NSGA-II 利用NSGA-II优化联邦学习中的通信开销

Applications of Evolutionary Computation : 17th European Conference, EvoApplications 2014, Granada, Spain, April 23-25, 2014 : revised selected papers. EvoApplications (Conference) (17th : 2014 : Granada, Spain) Pub Date : 2022-04-01 DOI: 10.48550/arXiv.2204.02183

José Á. Morell, Z. Dahi, F. Chicano, Gabriel Luque, E. Alba

{"title":"Optimising Communication Overhead in Federated Learning Using NSGA-II","authors":"José Á. Morell, Z. Dahi, F. Chicano, Gabriel Luque, E. Alba","doi":"10.48550/arXiv.2204.02183","DOIUrl":"https://doi.org/10.48550/arXiv.2204.02183","url":null,"abstract":"Federated learning is a training paradigm according to which a server-based model is cooperatively trained using local models running on edge devices and ensuring data privacy. These devices exchange information that induces a substantial communication load, which jeopardises the functioning efficiency. The difficulty of reducing this overhead stands in achieving this without decreasing the model's efficiency (contradictory relation). To do so, many works investigated the compression of the pre/mid/post-trained models and the communication rounds, separately, although they jointly contribute to the communication overload. Our work aims at optimising communication overhead in federated learning by (I) modelling it as a multi-objective problem and (II) applying a multi-objective optimization algorithm (NSGA-II) to solve it. To the best of the author's knowledge, this is the first work that texttt{(I)} explores the add-in that evolutionary computation could bring for solving such a problem, and texttt{(II)} considers both the neuron and devices features together. We perform the experimentation by simulating a server/client architecture with 4 slaves. We investigate both convolutional and fully-connected neural networks with 12 and 3 layers, 887,530 and 33,400 weights, respectively. We conducted the validation on the texttt{MNIST} dataset containing 70,000 images. The experiments have shown that our proposal could reduce communication by 99% and maintain an accuracy equal to the one obtained by the FedAvg Algorithm that uses 100% of communications.","PeriodicalId":91839,"journal":{"name":"Applications of Evolutionary Computation : 17th European Conference, EvoApplications 2014, Granada, Spain, April 23-25, 2014 : revised selected papers. EvoApplications (Conference) (17th : 2014 : Granada, Spain)","volume":"55 1","pages":"317-333"},"PeriodicalIF":0.0,"publicationDate":"2022-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88422585","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 6

The Asteroid Routing Problem: A Benchmark for Expensive Black-Box Permutation Optimization 小行星路线问题:昂贵黑盒排列优化的基准

Applications of Evolutionary Computation : 17th European Conference, EvoApplications 2014, Granada, Spain, April 23-25, 2014 : revised selected papers. EvoApplications (Conference) (17th : 2014 : Granada, Spain) Pub Date : 2022-03-29 DOI: 10.1007/978-3-031-02462-7_9

M. L'opez-Ib'anez, F. Chicano, R. Gil-Merino

引用次数: 2

Explainable Landscape Analysis in Automated Algorithm Performance Prediction 自动算法性能预测中的可解释景观分析

Applications of Evolutionary Computation : 17th European Conference, EvoApplications 2014, Granada, Spain, April 23-25, 2014 : revised selected papers. EvoApplications (Conference) (17th : 2014 : Granada, Spain) Pub Date : 2022-03-22 DOI: 10.48550/arXiv.2203.11828

R. Trajanov, Stefan Dimeski, Martin Popovski, P. Korošec, T. Eftimov

{"title":"Explainable Landscape Analysis in Automated Algorithm Performance Prediction","authors":"R. Trajanov, Stefan Dimeski, Martin Popovski, P. Korošec, T. Eftimov","doi":"10.48550/arXiv.2203.11828","DOIUrl":"https://doi.org/10.48550/arXiv.2203.11828","url":null,"abstract":"Predicting the performance of an optimization algorithm on a new problem instance is crucial in order to select the most appropriate algorithm for solving that problem instance. For this purpose, recent studies learn a supervised machine learning (ML) model using a set of problem landscape features linked to the performance achieved by the optimization algorithm. However, these models are black-box with the only goal of achieving good predictive performance, without providing explanations which landscape features contribute the most to the prediction of the performance achieved by the optimization algorithm. In this study, we investigate the expressiveness of problem landscape features utilized by different supervised ML models in automated algorithm performance prediction. The experimental results point out that the selection of the supervised ML method is crucial, since different supervised ML regression models utilize the problem landscape features differently and there is no common pattern with regard to which landscape features are the most informative.","PeriodicalId":91839,"journal":{"name":"Applications of Evolutionary Computation : 17th European Conference, EvoApplications 2014, Granada, Spain, April 23-25, 2014 : revised selected papers. EvoApplications (Conference) (17th : 2014 : Granada, Spain)","volume":"50 1","pages":"207-222"},"PeriodicalIF":0.0,"publicationDate":"2022-03-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76500734","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 6

Search Trajectories Networks of Multiobjective Evolutionary Algorithms 多目标进化算法的搜索轨迹网络

Applications of Evolutionary Computation : 17th European Conference, EvoApplications 2014, Granada, Spain, April 23-25, 2014 : revised selected papers. EvoApplications (Conference) (17th : 2014 : Granada, Spain) Pub Date : 2022-01-27 DOI: 10.1007/978-3-031-02462-7_15

Yuri Lavinas, C. Aranha, G. Ochoa

引用次数: 6

A Machine Learning-Based Approach for Economics-Tailored Applications: The Spanish Case Study 基于机器学习的经济学方法——量身定制的应用:西班牙案例研究

Applications of Evolutionary Computation : 17th European Conference, EvoApplications 2014, Granada, Spain, April 23-25, 2014 : revised selected papers. EvoApplications (Conference) (17th : 2014 : Granada, Spain) Pub Date : 2022-01-01 DOI: 10.1007/978-3-031-02462-7_36

Z. Dahi, Gabriel Luque, E. Alba

引用次数: 0

Self-adaptation of Neuroevolution Algorithms Using Reinforcement Learning 基于强化学习的神经进化算法的自适应

Applications of Evolutionary Computation : 17th European Conference, EvoApplications 2014, Granada, Spain, April 23-25, 2014 : revised selected papers. EvoApplications (Conference) (17th : 2014 : Granada, Spain) Pub Date : 2022-01-01 DOI: 10.1007/978-3-031-02462-7_29

Michael Kogan, Joshua Karns, Travis J. Desell

引用次数: 0

Ground-Truth Segmentation of the Spinal Cord from 3T MR Images Using Evolutionary Computation 基于进化计算的3T MR图像脊髓真值分割

Applications of Evolutionary Computation : 17th European Conference, EvoApplications 2014, Granada, Spain, April 23-25, 2014 : revised selected papers. EvoApplications (Conference) (17th : 2014 : Granada, Spain) Pub Date : 2022-01-01 DOI: 10.1007/978-3-031-02462-7_35

Mohamed Mounir E. L. Mendili, Noémie Villard, Brice Tiret, Raphaël Chen, D. Galanaud, Benoît Magnin, S. Lehéricy, P. Pradat, E. Lutton, S. Mesmoudi

引用次数: 0

EvoMCS: Optimising Energy and Throughput of Mission Critical Services EvoMCS:优化关键任务服务的能源和吞吐量

Applications of Evolutionary Computation : 17th European Conference, EvoApplications 2014, Granada, Spain, April 23-25, 2014 : revised selected papers. EvoApplications (Conference) (17th : 2014 : Granada, Spain) Pub Date : 2022-01-01 DOI: 10.1007/978-3-031-02462-7_16

Miguel Arieiro, Bruno Sousa

引用次数: 0

Brain Programming and Its Resilience Using a Real-World Database of a Snowy Plover Shorebird 基于雪鸻滨鸟真实世界数据库的大脑编程及其弹性

Applications of Evolutionary Computation : 17th European Conference, EvoApplications 2014, Granada, Spain, April 23-25, 2014 : revised selected papers. EvoApplications (Conference) (17th : 2014 : Granada, Spain) Pub Date : 2022-01-01 DOI: 10.1007/978-3-031-02462-7_38

Roberto Pineda, Gustavo Olague, Gerardo Ibarra-Vázquez, Axel Martinez, Jonathan Vargas, I. Reducindo

引用次数: 2