Conference Information

MLN 2026: International Conference on Machine Learning for Networking

Please Login to view website of conference
Free account: view official websites, track deadlines, and get email reminders.
Register Login
Submission Date:
2026-10-15 Closed
Notification Date:
2026-10-30
Conference Date:
2026-12-01
Location:
Paris, France
Years:
Viewed: 16988   Tracked: 0   Attend: 0
Something wrong with this page? Tell us
Embed deadline badge
MLN
Get this via API
Search and ranking lists need no credentials at all; full detail for this page needs a free API key. See the developer guide.

Conference Partner Index (CP-I)

50.0 / 100
Ranked #1,689 of 5,759 conferences · Top 30%

#172 of 751 in Artificial Intelligence & Machine Learning #240 of 874 in Networks & Communications

Academic recognition (35%) No data - scored at the neutral baseline of 50 —
Submission selectivity (20%) No data - scored at the neutral baseline of 50 —
Editions held (20%)
62
Community attention (10%)
18
Public record completeness (15%)
55

Inputs used: Editions on record: 9 · Researchers who opened this page in the past 24 months: 10

Missing from the public record: Historical acceptance rates (+4.5) · Best-paper records (+2.3)
Organizers can add these from this page after claiming the conference; scores are recomputed nightly. How to raise this score

Confidence 45% - the share of the score backed by observed data rather than the neutral baseline. How this score is calculated · Browse the ranking · Algorithm version 1.2 · Computed 2026-10-24

Call For Papers

MLN 2026 (International Conference on Machine Learning for Networking) is an academic conference held in Paris, France on 2026-12-01. The paper submission deadline is 2026-10-15. Acceptance notifications are sent on 2026-10-30.

MLN 2026 is the 9th International Conference on Machine Learning for Networking. The conference brings together researchers, practitioners, engineers, and industry experts working at the intersection of artificial intelligence, machine learning, communication networks, and distributed systems. MLN 2026 aims to foster multidisciplinary exchanges on the design, operation, optimization, security, and evolution of intelligent networks, as well as on the networking infrastructures required to support emerging AI systems. The conference welcomes original research contributions, experimental studies, system and prototype descriptions, industry experiences, datasets, benchmarks, and survey papers. MLN 2026 will be held in Paris, France, from December 1st to December 3rd, 2026. Artificial intelligence and machine learning are transforming the way communication networks are designed, deployed, operated, secured, and optimized. At the same time, the rapid development of foundation models, generative AI, agentic systems, and large-scale distributed learning is creating new networking requirements in terms of performance, scalability, reliability, energy efficiency, privacy, and security. MLN 2026 provides an international forum for presenting and discussing advances at the intersection of machine learning and networking. The scope of the conference encompasses two complementary perspectives: AI and machine learning for networks: the use of intelligent methods to analyze, automate, optimize, secure, and manage communication and distributed systems. Networks and distributed systems for AI: the design of communication infrastructures, protocols, architectures, and resource- management mechanisms that support AI training, inference, agent collaboration, and intelligent services. MLN 2026 encourages contributions that combine methodological advances with networking applications, as well as interdisciplinary work spanning artificial intelligence, telecommunications, distributed computing, cybersecurity, operations research, control, and data science. Authors are invited to submit complete unpublished papers, which are not under review in any other conference or journal, to https://easychair.org/conferences/?conf=mln2026. The accepted papers will be published as a post-proceedings in Springer's LNCS. Lecture Notes in Computer Science (LNCS) series is indexed by the ISI Conference Proceedings Citation Index - Science (CPCI-S), included in ISI Web of Science, EI Engineering Index (Compendex and Inspec databases), ACM Digital Library, dblp, Google Scholar, Scopus, etc. Topics of interest include and are not limited to: Machine Learning and Artificial Intelligence for Networks Deep, reinforcement, graph, federated, and distributed learning Traffic prediction, anomaly detection, routing, and resource allocation Machine learning for 5G, 6G, IoT, satellite, and wireless networks Intelligent SDN, NFV, cloud, edge, and service orchestration Energy-efficient and sustainable communications Agentic AI and Autonomous Network Management Agentic AI for network operations and optimization Autonomous, zero-touch, and intent-based networks Multi-agent coordination and collaboration AI agents for control, fault detection, and remediation Human-in-the-loop automation, safety, and governance Generative AI, Foundation Models, and Network Digital Twins Large language models and foundation models for networking Generative AI for network design and management RAG, knowledge graphs, and natural-language interfaces Network digital twins and synthetic data generation Multimodal and resource-efficient models for cloud and edge Networking and Distributed Systems for AI Networks for distributed AI training and inference Data-center, cloud, edge, and high-performance AI networking Efficient federated learning and collaborative inference Joint optimization of communication, computing, and energy Architectures and protocols for AI-agent ecosystems Security, Trustworthiness, Experimentation, and Applications Machine learning for network security and resilience Adversarial AI and security of autonomous agents Explainable, trustworthy, and privacy-preserving AI Datasets, benchmarks, testbeds, and real-world deployments Intelligent applications for smart and critical systems Position papers are also welcome and should be clearly marked as such.
Last updated by Admin Agent on

People who viewed this also viewed

Related Conferences

CCFICORECP-IShortFull NameSubmissionConference
CB77.3NetworkingInternational Conferences on Networking2026-02-082026-05-24
AA*95.8SIGIRInternational Conference on Research and Development in Information Retrieval2027-01-142027-07-18
AA*97.8AAAIAAAI Conference on Artificial Intelligence2026-07-212027-02-16
AA*94.7CVPRIEEE Conference on Computer Vision and Pattern Recognition2026-11-102027-06-20
BA*89.8ICRAInternational Conference on Robotics and Automation2026-09-152027-05-24
BA*97.6IJCAIInternational Joint Conference on Artificial Intelligence2027-01-042027-08-07
AA*93.0STOCACM Symposium on Theory of Computing2026-11-022027-06-06
C87.6ICCInternational Conference on Communications2026-10-022027-05-30
CB63.0IJCNNInternational Joint Conference on Neural Networks2027-01-312027-06-14
B91.2ICASSPInternational Conference on Acoustics, Speech and Signal Processing2026-09-162027-05-16

Related Journals

CCFFull NameImpact FactorPublisherISSN
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

Comments 0

No comments yet.

Please Login to post a comment