友情提示：以下期刊信息可能会有更新，仅供参考，请在投稿前自行登录期刊官网仔细核实。
期刊名
JOURNAL OF MACHINE LEARNING RESEARCH
J MACH LEARN RES
ISSN / eISSN
1532-4435 / 1533-7928
目标和范围
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JMLR seeks previously unpublished papers on machine learning that contain: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.
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JMLR seeks previously unpublished papers on machine learning that contain: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.
研究方向
自动化与控制系统
计算机：人工智能
CiteScore
18.80
查看趋势图
CiteScore 学科排名
| 类别 | 分区 | 排名 |
|---|---|---|
| Mathematics - Statistics and Probability | Q1 | #1/278 |
| Mathematics - Control and Systems Engineering | Q1 | #10/321 |
| Mathematics - Software | Q1 | #20/407 |
| Mathematics - Artificial Intelligence | Q1 | #20/350 |
Web of Science 核心收藏夹
| Science Citation Index Expanded (SCIE) | Social Sciences Citation Index (SSCI) |
|---|---|
| Indexed | - |
| 类别 (Journal Citation Reports 2024) | 分区 |
|---|---|
| AUTOMATION & CONTROL SYSTEMS | Q1 |
| COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE | Q2 |
H-index
173
出版国家或地区
UNITED STATES
出版商
Microtome Publishing
出版周期
Bimonthly
出版年份
2001
年文章数
349
Open Access
YES
通讯方式
MICROTOME PUBL, 31 GIBBS ST, BROOKLINE, USA, MA, 02446
认证评论
Find the ideal target journal for your manuscript
Explore over 38,000 international journals covering a vast array of academic fields.
SearchAdd your recorded webinar
Do you already have a recorded webinar? Grow your audience and get more views by easily listing your recording on Peeref.
Upload Now