官网链接:ecmlpkdd.org/2025/ Paper format Papers must be written in English and formatted in LaTeX, following the outline of our author kit Springer LNCS Template Download. The kit includes a readme document, a LaTeX file template containing author instructions, and style files. The maximum lengt...
ECML PKDD( European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases, CCF B) 2024于9月9号-9月13号正在立陶宛维尔纽斯举行(Vilnius) 本文总结了ECML PKDD 2024有关时空数据(spatial-temporal data)的相关论文,主要包含交通预测,预训练,迁移学习等内容,如有疏漏,欢迎...
https://2024.ecmlpkdd.org/submissions/journal-track Participating journal Journal Machine Learning Machine Learning is an international forum focusing on computational approaches to learning. Publishing model Hybrid Journal Impact Factor 4.3 (2023) Downloads 1.9M (2024) Submission to first decision...
ECML PKDD ECML - European Conference on Machine Learning and PKDD - Principles and Practice of Knowledge Discovery in Databases Publications can be submitted to and will be published in theproceedings track: Accepted papers will be published in the Lecture Notes in Artificial Intelligence (LNCS/LNAI...
ECML-PKDD 2025: The European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases
ECML PKDD 2024于9月9号-9月13号在立陶宛维尔纽斯举行(Vilnius) 本文总结了ECML PKDD 2024有关时空数据(spatial-temporal data)的相关论文,主要包含交通预测,预训练,迁移学习等内容,如有疏漏,欢迎大家补充。以及时间序列(time series),包括时序预测,异常检测,分类,聚类等内容。 Research Track 1. Spatiotemporal Cova...
ECML PKDD 2024 Participating journal: Data Mining and Knowledge Discovery Closed for submissions - Participating journal Journal Data Mining and Knowledge Discovery Data Mining and Knowledge Discovery is a leading technical journal focusing on the extraction of information from vast databases. Publishing...
·会议简称:ECML-PKDD 2022 ·截止日期: ·会议时间:2022年9月19日——23日 ·会议地点:法国-格勒诺布尔02会议主题 会议呼吁从Research和Applied Data Science两个track的研究论文。我们欢迎机器学习、知识发现和数据挖掘各个领域的研究文章。03主讲人INRIA- SIERRA project-team ...
以前ECML和AAAI，IJCAI，CIKM，ICDM，WSDM差不多，但是和PKDD合并之后，并没有实现1+1>2的效果。而且...
Multi-View Self-Supervised Heterogeneous Graph Embedding, 2021, ECML-PKDD 本文提出一种新的基于元路径的异构图自监督学习方法MVSE,采用两个视图intra-view和inter-view的对比学习。 实验的数据集是DBLP、ACM、IMDB。 2 方法论 2.1 模型总览 给定异构图中的一个结点,MVSE首先采样其基于元路径的子图,然后通过semant...