咨询与建议

限定检索结果

文献类型

  • 163 篇 期刊文献
  • 143 篇 会议
  • 7 篇 学位论文

馆藏范围

  • 313 篇 电子文献
  • 0 种 纸本馆藏

日期分布

学科分类号

  • 282 篇 工学
    • 255 篇 计算机科学与技术...
    • 50 篇 电气工程
    • 43 篇 软件工程
    • 30 篇 控制科学与工程
    • 15 篇 信息与通信工程
    • 8 篇 机械工程
    • 4 篇 交通运输工程
    • 4 篇 生物医学工程(可授...
    • 4 篇 安全科学与工程
    • 3 篇 电子科学与技术(可...
    • 3 篇 网络空间安全
    • 2 篇 仪器科学与技术
    • 2 篇 材料科学与工程(可...
    • 2 篇 石油与天然气工程
    • 2 篇 航空宇航科学与技...
    • 2 篇 环境科学与工程(可...
    • 2 篇 城乡规划学
    • 1 篇 力学(可授工学、理...
  • 66 篇 管理学
    • 66 篇 管理科学与工程(可...
  • 48 篇 理学
    • 34 篇 数学
    • 6 篇 物理学
    • 5 篇 生物学
    • 5 篇 系统科学
    • 2 篇 统计学(可授理学、...
  • 6 篇 医学
    • 5 篇 临床医学
  • 2 篇 经济学
    • 2 篇 应用经济学
    • 1 篇 理论经济学
  • 2 篇 法学
    • 1 篇 法学
    • 1 篇 政治学
    • 1 篇 社会学
  • 2 篇 农学

主题

  • 313 篇 algorithm select...
  • 53 篇 machine learning
  • 47 篇 meta-learning
  • 13 篇 combinatorial op...
  • 12 篇 automl
  • 12 篇 classification
  • 9 篇 hyperparameter o...
  • 9 篇 benchmarking
  • 9 篇 exploratory land...
  • 8 篇 algorithm config...
  • 8 篇 reinforcement le...
  • 8 篇 clustering
  • 8 篇 optimization
  • 7 篇 metalearning
  • 7 篇 instance space a...
  • 7 篇 black-box optimi...
  • 7 篇 software verific...
  • 7 篇 performance pred...
  • 7 篇 constraint progr...
  • 6 篇 algorithm portfo...

机构

  • 7 篇 univ melbourne s...
  • 7 篇 monash univ sch ...
  • 4 篇 itmo university
  • 4 篇 univ fed pernamb...
  • 4 篇 city univ hong k...
  • 4 篇 duke kunshan uni...
  • 4 篇 univ freiburg fr...
  • 3 篇 leiden univ liac...
  • 3 篇 tianjin normal u...
  • 3 篇 univ tecn federi...
  • 3 篇 ben gurion univ ...
  • 3 篇 paderborn univ h...
  • 3 篇 univ rennes inri...
  • 3 篇 eindhoven univ t...
  • 3 篇 ludwig maximilia...
  • 2 篇 edinburgh napier...
  • 2 篇 univ edinburgh s...
  • 2 篇 univ rostock d-1...
  • 2 篇 univ peshawar qa...
  • 2 篇 univ cordoba dep...

作者

  • 16 篇 smith-miles kate
  • 8 篇 soares carlos
  • 7 篇 munoz mario andr...
  • 7 篇 huellermeier eyk...
  • 7 篇 misir mustafa
  • 6 篇 trautmann heike
  • 6 篇 hart emma
  • 5 篇 sergey muravyov
  • 5 篇 tornede alexande...
  • 5 篇 prudencio ricard...
  • 5 篇 rokach lior
  • 5 篇 ali rahman
  • 5 篇 eftimov tome
  • 5 篇 wever marcel
  • 5 篇 andrey filchenko...
  • 4 篇 vanschoren joaqu...
  • 4 篇 van rijn jan n.
  • 4 篇 kirley michael
  • 4 篇 richter cedric
  • 4 篇 cenikj gjorgjina

语言

  • 306 篇 英文
  • 4 篇 其他
  • 2 篇 中文
  • 1 篇 德文
检索条件"主题词=algorithm selection"
313 条 记 录,以下是51-60 订阅
排序:
A sensor fusion framework for online sensor and algorithm selection
收藏 引用
ROBOTICS AND AUTONOMOUS SYSTEMS 2008年 第9期56卷 762-776页
作者: Cohen, Ofir Edan, Yael Ben Gurion Univ Negev Dept Ind Engn & Management IL-84105 Beer Sheva Israel Ben Gurian Int Airport Israel Aircraft Ind Ltd Mil Aircraft Grp Lahav Div IL-70100 Beer Sheva Israel
This paper presents a sensor fusion framework framework for selecting online the most reliable logical sensors and the most suitable algorithm for fusing sensor data in a robot platform. The framework is rule-based, e... 详细信息
来源: 评论
A PAC APPROACH TO APPLICATION-SPECIFIC algorithm selection
收藏 引用
SIAM JOURNAL ON COMPUTING 2017年 第3期46卷 992-1017页
作者: Gupta, Rishi Roughgarden, Tim Stanford Univ Dept Comp Sci Stanford CA 94305 USA
The best algorithm for a computational problem generally depends on the "relevant inputs," a concept that depends on the application domain and often defies formal articulation. While there is a large body o... 详细信息
来源: 评论
Reducing Cognitive Overload by Meta-Learning Assisted algorithm selection
收藏 引用
INTERNATIONAL JOURNAL OF COGNITIVE INFORMATICS AND NATURAL INTELLIGENCE 2008年 第3期2卷 90-100页
作者: Fan, Lisa Lei, Minxiao Univ Regina Regina SK Canada
With the explosion of aver/able data mining algorithms, a method 'Or helping user to select the most appropriate algorithm or combination of algorithms to solve a given problem and reducing users' cognitive ov... 详细信息
来源: 评论
When algorithm selection meets Bi-linear Learning to Rank: accuracy and inference time trade off with candidates expansion
收藏 引用
INTERNATIONAL JOURNAL OF DATA SCIENCE AND ANALYTICS 2023年 第2期16卷 173-189页
作者: Yuan, Jing Geissler, Christian Shao, Weijia Lommatzsch, Andreas Jain, Brijnesh Tech Univ Berlin TEL-14Ernst Reuter Pl 7 D-10587 Berlin Germany
algorithm selection (AS) tasks are dedicated to find the optimal algorithm for an unseen problem instance. With the knowledge of problem instances' meta-features and algorithms' landmark performances, Machine ... 详细信息
来源: 评论
MetaStream: A meta-learning based method for periodic algorithm selection in time-changing data
收藏 引用
NEUROCOMPUTING 2014年 第1期127卷 52-64页
作者: Debiaso Rossi, Andre Luis de Leon Ferreira de Carvalho, Andre Carlos Ponce Soares, Carlos de Souza, Bruno Feres Univ Sao Paulo Inst Ciencias Matemat & Computac Sao Carlos SP Brazil Univ Porto Fac Engn INESC TEC P-4100 Oporto Portugal
Dynamic real-world applications that generate data continuously have introduced new challenges for the machine learning community, since the concepts to be learned are likely to change over time. In such scenarios, an... 详细信息
来源: 评论
Automated algorithm selection: from Feature-Based to Feature-Free Approaches
收藏 引用
JOURNAL OF HEURISTICS 2023年 第1期29卷 1-38页
作者: Alissa, Mohamad Sim, Kevin Hart, Emma Edinburgh Napier Univ Sch Comp Edinburgh Scotland
We propose a novel technique for algorithm-selection, applicable to optimisation domains in which there is implicit sequential information encapsulated in the data, e.g., in online bin-packing. Specifically we train t... 详细信息
来源: 评论
Deep Reinforcement Learning for Dynamic algorithm selection: A Proof-of-Principle Study on Differential Evolution
收藏 引用
IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS 2024年 第7期54卷 4247-4259页
作者: Guo, Hongshu Ma, Yining Ma, Zeyuan Chen, Jiacheng Zhang, Xinglin Cao, Zhiguang Zhang, Jun Gong, Yue-Jiao South China Univ Technol Sch Comp Sci & Engn Guangzhou 510006 Peoples R China Natl Univ Singapore Coll Design & Engn Dept Ind Syst Engn & Management Singapore Singapore Singapore Management Univ Sch Comp & Informat Syst Singapore Singapore Nankai Univ Tianjin 300192 Peoples R China Hanyang Univ Seoul 04763 South Korea Univ Victoria Melbourne Vic 3004 Australia
Evolutionary algorithms, such as differential evolution, excel in solving real-parameter optimization challenges. However, the effectiveness of a single algorithm varies across different problem instances, necessitati... 详细信息
来源: 评论
Cascaded algorithm selection With Extreme-Region UCB Bandit
收藏 引用
IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE 2022年 第10期44卷 6782-6794页
作者: Hu, Yi-Qi Liu, Xu-Hui Li, Shu-Qiao Yu, Yang Nanjing Univ Natl Key Lab Novel Software Technol Nanjing 210023 Jiangsu Peoples R China Pazhou Lab Guangzhou 510330 Guangdong Peoples R China Polixir Ai Nanjing 210046 Jiangsu Peoples R China
AutoML aims at best configuring learning systems automatically. It contains core subtasks of algorithm selection and hyper-parameter tuning. Previous approaches considered searching in the joint hyper-parameter space ... 详细信息
来源: 评论
Empirical hardness of finding optimal Bayesian network structures: algorithm selection and runtime prediction
收藏 引用
MACHINE LEARNING 2018年 第1期107卷 247-283页
作者: Malone, Brandon Kangas, Kustaa Jarvisalo, Matti Koivisto, Mikko Myllymaki, Petri NEC Labs Europe Heidelberg Germany Univ Helsinki HIIT Dept Comp Sci Helsinki Finland
Various algorithms have been proposed for finding a Bayesian network structure that is guaranteed to maximize a given scoring function. Implementations of state-of-the-art algorithms, solvers, for this Bayesian networ... 详细信息
来源: 评论
The algorithm selection competitions 2015 and 2017
收藏 引用
ARTIFICIAL INTELLIGENCE 2019年 272卷 86-100页
作者: Lindauer, Marius van Rijn, Jan N. Kotthoff, Lars Univ Freiburg Freiburg Germany Columbia Univ New York NY 10027 USA Univ Wyoming Laramie WY 82071 USA
The algorithm selection problem is to choose the most suitable algorithm for solving a given problem instance. It leverages the complementarity between different approaches that is present in many areas of Al. We repo... 详细信息
来源: 评论