会议信息

ICMLCN 2025: IEEE International Conference on Machine Learning for Communication and Networking

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ICMLCN
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截稿日期:
2024-10-31
通知日期:
2025-01-31
会议日期:
2025-05-26
会议地点:
Barcelona, Spain
届数:
2
浏览: 12807   关注: 0   参加: 0

会伴指数 (CP-I)

39.7 / 100
全站第 5,082 名 / 共 5,647 个会议 · 前 90%

人工智能与机器学习 第 647 / 734 网络与通信 第 782 / 861

学术认可 (35%) 无数据 —— 按中性基准 50 分计入 —
投稿选择性 (20%) 无数据 —— 按中性基准 50 分计入 —
会议传承 (20%)
30
社区关注 (10%)
10
资料公开度 (15%)
35

用到的输入: 有据可查的届次：2 · 过去 24 个月打开过本页的研究者：3 人

公开资料里还缺: 历年录用率 (+4.5) · 历届信息 (+3.0) · 最佳论文记录 (+2.3)
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 45% —— 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 2026-09-02

征稿

ICMLCN 2025 (IEEE International Conference on Machine Learning for Communication and Networking) is an academic conference held in Barcelona, Spain on 2025-05-26. The paper submission deadline is 2024-10-31. Acceptance notifications are sent on 2025-01-31.

The second IEEE International Conference on Machine Learning in Communications and Networking will be held in Barcelona, Spain. The conference brings together researchers from the disciplines of Machine Learning (ML), Communication and Networking and Signal Processing, and aims at promoting fundamental and applied research of ML for designing and analyzing communication systems and networks, for developing communication protocols to support ML services, as well as for advancing distributed ML over communication networks. The conference targets any communication and networking area, such as, but not limited to, wireless, satellite, optical, or molecular communications, Internet, and WLAN. TOPICS • ML and molecular networks • ML and optical networks • ML in Intelligent reflecting surfaces • ML and networking in smart cities • Decentralized transmission optimization for edge learning • Distributed multi-agent reinforcement learning • Edge learning in wireless networks • Experiments and testbeds • Integrated distributed optimization with edge learning • Integrated sensing and communication via ML • Network architectures and protocols for edge learning • Over-the-air computation for edge learning • Privacy and security issues with ML over networks • Trustworthiness in ML decisions • ML and networking for intelligent transportation systems • ML and networking for smart grids • ML for signal processing in communication and networking • ML for the MAC layer • ML for the physical layer • ML for the transport layer • Communication-efficient distributed ML • Distributed ML over communication networks • Federated learning and communications • Learn to transmit and receive • Resource management and network optimization • Semantic communications and ML • Wireless communication to support ML services • Wireless networking to support ML services • ML and IoT • Large language models (LLMs) for communication and networking
由 Dou Sun 最后更新于

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相关期刊

CCF全称影响因子出版商ISSN
BMachine Learning2.9Springer0885-6125
AIEEE Transactions on Multimedia9.7IEEE1520-9210
CKnowledge-Based Systems7.2Elsevier0950-7051
BSoftware & Systems Modeling3.2Springer1619-1366
AIEEE Transactions on Computers3.8IEEE0018-9340
CFuture Generation Computer Systems5.9Elsevier0167-739X
CNeurocomputing6.5Elsevier0925-2312
CPattern Recognition Letters3.9Elsevier0167-8655
BPattern Recognition7.6Elsevier0031-3203
IEEE Access3.6IEEE2169-3536

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