检索结果-内蒙古大学图书馆

您好，读者！请登录

内蒙古大学图书馆

首页
概况
党建
资源
服务
科研支持
- 论文收录引用证明
- 科技查新
知识产权
档案馆
帮助

咨询与建议

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

您的常用邮箱：*

您的手机号码：*

问题描述：

当前已输入0个字，您还可以输入200个字

全部搜索
期刊论文
图书
学位论文
标准
纸本馆藏
外文资源发现
数据库导航
超星发现

高级检索

时间限定

出版年份：

文献类型

图书期刊文献学位论文多媒体

馆藏选择

电子馆藏纸本馆藏

核心期刊

全部期刊 SCI 收录期刊 SSCI 收录期刊 EI 收录期刊 CSCD 收录期刊 CSSCI 收录期刊

语言

中文英文

文献类型

期刊文献图书学位论文标准纸本馆藏

帮助

文字说明：

T=题名（书名、题名），A=作者（责任者），K=主题词，P=出版物名称，PU=出版社名称，O=机构（作者单位、学位授予单位、专利申请人），L=中图分类号，C=学科分类号，U=全部字段，Y=年（出版发行年、学位年度、标准发布年）

检索规则说明：

AND代表“并且”；OR代表“或者”；NOT代表“不包含”；(注意必须大写,运算符两边需空一格)

检索范例：

范例一：(K=图书馆学 OR K=情报学) AND A=范并思 AND Y=1982-2016
范例二：P=计算机应用与软件 AND (U=C++ OR U=Basic) NOT K=Visual AND Y=2011-2016

分类表

所选分类

>> <<

限定检索结果

文献类型

3 篇 会议

馆藏范围

3 篇 电子文献
0 种 纸本馆藏

日期分布

学科分类号

3 篇 工学
- 3 篇 计算机科学与技术...
- 1 篇 电气工程

主题

3 篇 asynchronous par...
2 篇 genetic programm...
1 篇 multi-objective
1 篇 hyper-heuristics
1 篇 automated machin...
1 篇 neural architect...
1 篇 cartesian geneti...
1 篇 evolutionary com...
1 篇 parallel evoluti...
1 篇 sat

机构

1 篇 washington univ ...
1 篇 missouri univ sc...
1 篇 missouri univ sc...
1 篇 east china norma...

作者

2 篇 tauritz daniel r...
1 篇 bertels alex r.
1 篇 wang wei
1 篇 hu mengtao
1 篇 siever william m...
1 篇 liu li
1 篇 liu yao
1 篇 harter adam

语言

3 篇 英文

检索条件"主题词=Asynchronous Parallel Evolution"

共 3 条记录，以下是1-10 订阅

全选清除本页清除全部题录导出标记到"检索档案"

详细简洁

排序：

Why asynchronous parallel evolution is the Future of Hyper-heuristics: A CDCL SAT Solver Case Study

Why Asynchronous Parallel Evolution is the Future of Hyper-h...

引用

Genetic and evolutionary Computation Conference (GECCO)

作者： Bertels, Alex R. Tauritz, Daniel R. Missouri Univ Sci & Technol Dept Comp Sci Nat Computat Lab Rolla MO 65409 USA

ISBN: (纸本)9781450343237

evolutionary Algorithms (EAs) are inherently parallel due to their ability to simultaneously evaluate the fitness of individuals. Synchronous parallel EAs (SPEAs) leverage this with the intent to gain significant speed-ups when executed on multiple processors. However, many important problem classes lead to large variations in fitness evaluation times, such as is often the case in hyper-heuristics where the time complexity of executing one individual may differ greatly from that of another. asynchronous parallel EAs (APEAs) omit the generational synchronization step of traditional EAs which work in well-defined cycles. They can provide scalability improvements proportional to the variation in fitness evaluation times of the evolved individuals, and therefore should be considered for use in hyper-heuristics. This paper provides an empirical analysis of the improvements obtained by applying APEAs, compared to SPEAs, on a case study involving the evolution of conflict-driven clause learning Boolean satisfiability solvers, demonstrating that APEAs are the future of hyper-heuristics.

关键词： Hyper-Heuristics asynchronous parallel evolution parallel evolutionary Algorithms Genetic Programming SAT

来源：评论

学校读者我要写书评

暂无评论

APENAS: An asynchronous parallel evolution Based Multi-objective Neural Architecture Search 18

APENAS: An Asynchronous Parallel Evolution Based Multi-objec...

引用

18th IEEE Int Symp on parallel and Distributed Proc with Applicat (ISPA) / 10th IEEE Int Conf on Big Data and Cloud Comp (BDCloud) / IEEE Int Symp on Social Comp and Networking (SocialCom) / IEEE Int Conf on Sustainable Comp and Commun (SustainCom)

作者： Hu, Mengtao Liu, Li Wang, Wei Liu, Yao East China Normal Univ Sch Data Sci & Engn Shanghai Peoples R China

ISBN: (纸本)9781665414852

Machine learning is widely used in pattern classification, image processing and speech recognition. Neural architecture search (NAS) could reduce the dependence of human experts on machine learning effectively. Due to the high complexity of NAS, the tradeoff between time consumption and classification accuracy is vital. This paper presents APENAS, an asynchronous parallel evolution based multi-objective neural architecture search, using the classification accuracy and the number of parameters as objectives, encoding the network architectures as individuals. To make full use of computing resource, we propose a multi-generation undifferentiated fusion scheme to achieve asynchronous parallel evolution on multiple GPUs or CPUs, which speeds up the process of NAS. Accordingly, we propose an election pool and a buffer pool for two-layer filtration of individuals. The individuals are sorted in the election pool by non-dominated sorting and filtered in the buffer pool by the roulette algorithm to improve the elitism of the Pareto front. APENAS is evaluated on the CIFAR-10 and CIFAR-100 datasets [25]. The experimental results demonstrate that APENAS achieves 90.05% accuracy on CIFAR-10 with only 0.07 million parameters, which is comparable to state of the art. Especially, APENAS has high parallel scalability, achieving 92.5% parallel efficiency on 64 nodes.

关键词： automated machine learning neural architecture search multi-objective asynchronous parallel evolution

来源：评论

学校读者我要写书评

暂无评论

asynchronous parallel Cartesian Genetic Programming 17

Asynchronous Parallel Cartesian Genetic Programming

引用

Genetic and evolutionary Computation Conference (GECCO)

作者： Harter, Adam Tauritz, Daniel R. Siever, William M. Missouri Univ Sci & Technol Dept Comp Sci Nat Computat Lab Rolla MO 65401 USA Washington Univ Dept Comp Sci & Engn St Louis MO 63130 USA

ISBN: (纸本)9781450349390

The run-time of evolutionary algorithms (EAs) is typically dominated by fitness evaluation. This is particularly the case when the genotypes are complex, such as in genetic programming (GP). Evaluating multiple offspring in parallel is appropriate in most types of EAs and can reduce the time incurred by fitness evaluation proportional to the number of parallel processing units. The most naive approach maintains the synchrony of evolution as employed by the vast majority of EAs, requiring an entire generation to be evaluated before progressing to the next generation. Heterogeneity in the evaluation times will degrade the performance, as parallel processing units will idle until the longest evaluation has completed. asynchronous parallel evolution mitigates this bottleneck and techniques which experience high heterogeneity in evaluation times, such as Cartesian GP (CGP), are prime candidates for asynchrony. However, due to CGP's small population size, asynchrony has a significant impact on selection pressure and biases evolution towards genotypes with shorter execution times, resulting in poorer results compared to their synchronous counterparts. This paper: 1) provides a quick introduction to CGP and asynchronous parallel evolution, 2) introduces asynchronous parallel CGP, and 3) shows empirical results demonstrating the potential for asynchronous parallel CGP to outperform synchronous parallel CGP.

关键词： Genetic Programming asynchronous parallel evolution Cartesian Genetic Programming evolutionary Computing

来源：评论

学校读者我要写书评

暂无评论

没有更多数据了...

全选清除本页清除全部题录导出标记到“检索档案”

共1页 << < 1 > >>

检索报告对象比较合并检索0

隐藏清空

合并搜索

回到顶部

执行限定条件

内容：

评分：

请选择保存的检索档案：

请选择收藏分类：

订阅名称：

通借通还

温馨提示：

图书名称：

借书校区：

取书校区：

手机号码：

邮箱地址：

一卡通帐号：

电话和邮箱必须正确填写，我们会与您联系确认。

联系人：

所在院系：

联系邮箱：

联系电话：

内蒙古自治区呼和浩特市赛罕区大学西街235号邮编: 010021

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：