Bridging supervised learning and test-based co-optimization
IF 4.3
3区 计算机科学
Q1 AUTOMATION & CONTROL SYSTEMS
引用次数: 0
Abstract
This paper takes a close look at the important commonalities and subtle differences between the well-established field of supervised learning and the much younger one of cooptimization. It explains...桥梁监督学习和基于测试的协同优化
本文仔细研究了建立良好的监督学习领域与更年轻的协同优化领域之间的重要共同点和细微差异。它解释了……
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来源期刊
Journal of Machine Learning Research
工程技术-计算机：人工智能
CiteScore
18.80
自引率
0.00%
发文量
2
审稿时长
3 months
期刊介绍：
The Journal of Machine Learning Research (JMLR) provides an international forum for the electronic and paper publication of high-quality scholarly articles in all areas of machine learning. All published papers are freely available online.
JMLR has a commitment to rigorous yet rapid reviewing.
JMLR seeks previously unpublished papers on machine learning that contain:
new principled algorithms with sound empirical validation, and with justification of theoretical, psychological, or biological nature;
experimental and/or theoretical studies yielding new insight into the design and behavior of learning in intelligent systems;
accounts of applications of existing techniques that shed light on the strengths and weaknesses of the methods;
formalization of new learning tasks (e.g., in the context of new applications) and of methods for assessing performance on those tasks;
development of new analytical frameworks that advance theoretical studies of practical learning methods;
computational models of data from natural learning systems at the behavioral or neural level; or extremely well-written surveys of existing work.
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