7th KuVS Fachgespräch on Machine Learning in Networking (MaLeNe 2026)

MaLeNe 2026 aims to provide a forum for researchers addressing emerging concepts and challenges related to machine learning in networking. The Fachgespräch will address opportunities where machine learning can bring benefits to networking in different facets, such as network monitoring, management, and security. Together with flexible and programmable networks, this paves the way toward a more proactive and autonomous network design and “self-driving” networks. The long-term vision is that configuration decisions can be made in real time in an automated fashion before service and experience degradation occurs. The Fachgespräch will feature original paper presentations that foster discussions and joint work among participants.

Topics of Interest

Authors are invited to submit extended abstracts, early-stage research ideas, or work in progress related to the topic areas listed below:

Methodology

• Data sets for benchmarking, verification, proof of concept
• Data augmentation; dimensionality reduction (e.g., autoencoder); prediction and generation (e.g., GANs)
• Performance evaluation methodology (best practices)

Artificial Intelligence and Machine Learning Methods

• Classical and deep learning methods for supervised, unsupervised, and reinforcement learning
• Advanced methods (e.g., self-supervised learning) and models (e.g., adversarial, agentic, generative)
• Large language models and foundation models; tiny models

Generalizability

• Transfer of trained models (e.g., small to large networks, enterprise to data center)
• Federated learning (combine models trained for different data sets) and privacy
• Context drift, catastrophic forgetting, and machine unlearning

Explainability

• Explainable Artificial Intelligence (XAI) and visualization
• Understanding decisions of ML-based systems (management, traffic engineering, etc.)
• Game-theory-based approaches to approximate guarantees

Networking for Machine Learning and AI

• Network architectures, applications, and use cases (data center, enterprise, etc.)
• Network resource management (algorithms, schedulers, etc.)
• In-network computation and processing

Applications in Networking

• Network monitoring, especially from encrypted traffic (e.g., traffic classification, QoE)
• Network configuration (e.g., suggest optimal configurations, “spell-check” text-based configuration data)
• Network planning (e.g., reconfigurable data centers, job placement)
• Network management (e.g., autonomous management, self-driving networks)
• Network security (e.g., intrusion detection, covert channels, firewall)
• Advanced networks (e.g., 5G to 6G, industry, slicing)

Paper Submission

Authors may submit extended abstracts, early-stage research ideas, or works in progress presenting original research, ongoing studies, or practical experiences. Previously published work or work currently under review elsewhere cannot be submitted. Each submission must be written in English, accompanied by a 75 to 200 word abstract and a list of up to 5 key words. There is a length limitation of 2 A4 (210 mm × 297 mm) pages for full papers (including title, abstract, figures, tables) plus 1 page for references. Submissions must be in 2-column IEEE conference style with a minimum font size of 10 pt. Papers exceeding these limits, multiple submissions, and self-plagiarized papers will be rejected without further review. Authors should submit their papers electronically via the EasyChair online submission system under the following link: https://easychair.org/conferences?conf=malene2026

Important Dates

• Extended paper submission deadline: January 22, 2026 (final)