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检索条件"主题词=algorithm selection"
313 条 记 录,以下是181-190 订阅
排序:
Artificial Neural Networks as Feature Extractors in Continuous Evolutionary Optimization
Artificial Neural Networks as Feature Extractors in Continuo...
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International Joint Conference on Neural Networks (IJCNN)
作者: Friess, Stephen Tino, Peter Xu, Zhao Menzel, Stefan Sendhoff, Bernhard Yao, Xin Univ Birmingham Sch Comp Sci CERCIA Birmingham W Midlands England NEC Labs Europe GmbH D-69115 Heidelberg Germany Honda Res Inst Europe GmbH D-63073 Offenbach Germany Southern Univ Sci & Technol Shenzhen Peoples R China
Recent years have seen the advancement of data-driven paradigms in population-based and evolutionary optimization. This reflects on one hand the mere abundance of available data, but on the other hand also progresses ... 详细信息
来源: 评论
Improved Automated CASH Optimization with Tree Parzen Estimators for Class Imbalance Problems  8
Improved Automated CASH Optimization with Tree Parzen Estima...
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8th IEEE International Conference on Data Science and Advanced Analytics (DSAA)
作者: Duc Anh Nguyen Kong, Jiawen Wang, Hao Menzel, Stefan Sendhoff, Bernhard Kononova, Anna, V Baeck, Thomas Leiden Univ Leiden Inst Adv Comp Sci LIACS Leiden Netherlands Honda Res Inst Europe GmbH HRI EU Offenbach Germany
The imbalanced classification problem is very relevant in both academic and industrial applications. The task of finding the best machine learning model to use for a specific imbalanced dataset is complicated due to a... 详细信息
来源: 评论
FLOPs as a Discriminant for Dense Linear Algebra algorithms  22
FLOPs as a Discriminant for Dense Linear Algebra Algorithms
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Proceedings of the 51st International Conference on Parallel Processing
作者: Francisco López Lars Karlsson Paolo Bientinesi Department of Computing Science Umeå Universitet Sweden
Expressions that involve matrices and vectors, known as linear algebra expressions, are commonly evaluated through a sequence of invocations to highly optimised kernels provided in libraries such as BLAS and LAPACK. A... 详细信息
来源: 评论
A comparative study between SA and GA in solving MTSP
A comparative study between SA and GA in solving MTSP
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作者: Wenze Zhang Chenyang Xu Electrical and Computer engineering National University of Singapore Mechanical Engineering Shanghai Institute of Technology
The multiple traveling salesmen problems(MTSP) is a combinatorial optimization and np-hard problem. In practice, the computational resource required to solve such problems is usually prohibitive, and, in most cases, u... 详细信息
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ACO with automatic parameter selection for a scheduling problem with a group cumulative constraint
ACO with automatic parameter selection for a scheduling prob...
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Genetic and Evolutionary Computation Conference (GECCO)
作者: Groleaz, Lucas Ndiaye, Samba N. Solnon, Christine CNRS Infol LIRIS UMR5201 INSA Lyon F-69621 Villeurbanne France Univ Lyon 1 CITI INRIA UMR5201CNRSLIRIS F-69621 Villeurbanne France INSA Lyon CITI INRIA CHROMA F-69621 Villeurbanne France
We consider a RCPSP (resource constrained project scheduling problem), the goal of which is to schedule jobs on machines in order to minimise job tardiness. This problem comes from a real industrial application, and i... 详细信息
来源: 评论
Automatic recommendation of feature selection algorithms based on dataset characteristics
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EXPERT SYSTEMS WITH APPLICATIONS 2021年 185卷 115589-115589页
作者: Sabino Parmezan, Antonio Rafael Lee, Huei Diana Spolaor, Newton Wu, Feng Chung Univ Sao Paulo Inst Math & Comp Sci Lab Computat Intelligence Av Trabalhador Sao Carlense 400 BR-13566590 Sao Carlos SP Brazil Western Parana State Univ Engn & Exact Sci Ctr Lab Bioinformat Av Tarquinio Joslin dos Santos 1300 BR-85867900 Foz Do Iguacu PR Brazil Univ Estadual Campinas Fac Med Sci Coloproctol Serv Rua Tessalia Vieira de Camargo 126 BR-13083887 Campinas SP Brazil
Feature selection in real-world data mining problems is essential to make the learning task efficient and more accurate. Identifying the best feature selection algorithm, among the many available, is a complex activit... 详细信息
来源: 评论
LiBRe: Label-Wise selection of Base Learners in Binary Relevance for Multi-label Classification  18th
LiBRe: Label-Wise Selection of Base Learners in Binary Relev...
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18th International Symposium on Intelligent Data Analysis (IDA)
作者: Wever, Marcel Tornede, Alexander Mohr, Felix Hullermeier, Eyke Paderborn Univ Heinz Nixdorf Inst Paderborn Germany Univ La Sabana Cundinamarca Colombia
In multi-label classification (MLC), each instance is associated with a set of class labels, in contrast to standard classification, where an instance is assigned a single label. Binary relevance (BR) learning, which ... 详细信息
来源: 评论
Generating New Space-Filling Test Instances for Continuous Black-Box Optimization
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EVOLUTIONARY COMPUTATION 2020年 第3期28卷 379-404页
作者: Munoz, Mario A. Smith-Miles, Kate Univ Melbourne Sch Math & Stat Parkville Vic 3010 Australia
This article presents a method to generate diverse and challenging new test instances for continuous black-box optimization. Each instance is represented as a feature vector of exploratory landscape analysis measures.... 详细信息
来源: 评论
Selecting appropriate machine learning methods for digital soil mapping
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APPLIED MATHEMATICAL MODELLING 2020年 第0期81卷 401-418页
作者: Khaledian, Yones Miller, Bradley A. Iowa State Univ Dept Agron Ames IA 50011 USA
Digital soil mapping (DSM) increasingly makes use of machine learning algorithms to identify relationships between soil properties and multiple covariates that can be detected across landscapes. Selecting the appropri... 详细信息
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Personalized recommendation framework design for online tourism: know you better than yourself
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INDUSTRIAL MANAGEMENT & DATA SYSTEMS 2020年 第11期120卷 2067-2079页
作者: Wang, Xiaoqian Hubei Univ Econ Sch Tourism & Hotel Management Wuhan Peoples R China
Purpose This study aims to create an idea and a framework to enhance customer stickiness and improve transformation efficiency flow of tourism products from online to offline platforms through the application of perso... 详细信息
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