会议信息

COLT 2026: Annual Conference on Learning Theory

请登录查看会议网址
免费注册：查看官网链接、跟踪截稿日期，并接收邮件提醒。
注册 登录
嵌入截止倒计时徽章
COLT
用 API 获取这条数据
搜索与榜单列表完全无需凭证；本页的完整详情需要一把免费 API 密钥。详见开发者接入页。
截稿日期:
2026-02-04
通知日期:
2026-05-04
会议日期:
2026-06-29
会议地点:
San Diego, California, USA
届数:
39
CCF: B   ICORE: A*   QUALIS: A2   浏览: 367004   关注: 114   参加: 14

会伴指数 (CP-I)

89.2 / 100
全站第 83 名 / 共 5,682 个会议 · 前 2%

人工智能与机器学习 第 9 / 739

学术认可 (35%)
100
投稿选择性 (20%)
79
会议传承 (20%)
99
社区关注 (10%)
65
资料公开度 (15%)
80

用到的输入: 收录等级：CCF B, QUALIS A2 · 录用率：29.3%（有记录的 5 届的均值） · 有据可查的届次：39 · 在会伴关注它的研究者：114 人 · 过去 24 个月打开过本页的研究者：12 人

公开资料里还缺: 历届信息 (+3.0)
主办方认领本会议后，可直接在这一页补上；分数每晚重算。如何提升这个分数

置信度 100% —— 分数中有多大比例来自实际观测到的数据，而不是中性基准。 这个分数是怎么算出来的 · 查看完整榜单 · 算法版本 1.1 · 算于 2026-09-18

征稿

COLT 2026 (Annual Conference on Learning Theory) is a CCF B / ICORE A* / QUALIS A2 conference held in San Diego, California, USA on 2026-06-29. The paper submission deadline is 2026-02-04. Acceptance notifications are sent on 2026-05-04.

The 39th Annual Conference on Learning Theory (COLT 2026) will take place June 29-July 3, 2026 in San Diego, USA. We invite submissions of papers addressing theoretical aspects of machine learning, broadly defined as a subject at the intersection of computer science, statistics and applied mathematics. We strongly support an inclusive view of learning theory, including fundamental theoretical aspects of learnability in various contexts, and theory that sheds light on empirical phenomena. The topics include but are not limited to: Design and analysis of learning algorithms Statistical and computational complexity of learning Optimization methods for learning, including online and stochastic optimization Theory of artificial neural networks, including deep learning Theoretical explanation of empirical phenomena in learning Supervised learning Unsupervised, semi-supervised learning, domain adaptation Learning geometric and topological structures in data, manifold learning Active and interactive learning Reinforcement learning Online learning and decision-making Interactions of learning theory with other mathematical fields High-dimensional and non-parametric statistics Kernel methods Causality Sampling Theoretical analysis of probabilistic graphical models Bayesian methods in learning Game theory and learning Learning with system constraints (e.g., privacy, fairness, memory, communication) Learning from complex data (e.g., networks, time series) Learning in neuroscience, social science, economics and other subjects Quantum learning theory Submissions by authors who are new to COLT are encouraged. While the primary focus of the conference is theoretical, authors are welcome to support their analysis with relevant experimental results. Accepted papers will be presented at the conference. At least one author of each accepted paper should present the work at the conference. Accepted papers will be published electronically in the Proceedings of Machine Learning Research (PMLR). Authors of accepted papers will have the option of opting out of the proceedings in favor of a 1-page extended abstract, which will point to an open access archival version of the full paper reviewed for COLT.
由 Dou Sun 最后更新于

录用率

平均录用率: 36.7% 17 年间 (2000–2020).

年份提交数录用数录用率(%)
202038812030.9%
201939311830%
20183359127.2%
20172287432.5%
20162035326.1%
20151786234.8%
20141405237.1%
20131314735.9%
20121264132.5%
20081264434.9%
2007924144.6%
20061024342.2%
20051204537.5%
20041074441.1%
2003924953.3%
2002552647.3%
20001726236%

最佳论文

看过这个的人也在看

CCFICORECP-I简称全称截稿日期会议日期
AA*96.8The Web ConferenceThe ACM Web Conference2026-10-182027-05-10
BB92.7COLINGInternational Conference on Computational Linguistics2026-10-122027-05-09

相关会议

相关期刊

CCF全称影响因子出版商ISSN
BSoftware & Systems Modeling3.2Springer1619-1366
BPattern Recognition7.6Elsevier0031-3203
BIEEE Transactions on Neural Networks and Learning Systems8.9IEEE1045-9227
BInformation Sciences6.0Elsevier0020-0255
BComputer Networks4.7Elsevier1389-1286
BComputers & Security5.4Elsevier0167-4048
BIEEE Transactions on Intelligent Transportation Systems8.4IEEE1524-9050
BJournal of Systems and Software3.8Elsevier0164-1212
BInformation Processing & Management6.9Elsevier0306-4573
BIEEE Transactions on Robotics10.5IEEE1552-3098

评论 0

暂无评论。

请登录后发表评论