:: Library Catalog

Copertina

Salvato in:

Dettagli Bibliografici
Autori principali:	Duan, Tao, Zhao, Junzhou, Zhang, Shuo, Tao, Jing, Wang, Pinghui
Natura:	Preprint
Pubblicazione:	2024
Soggetti:	Machine Learning Networking and Internet Architecture
Accesso online:	https://arxiv.org/abs/2404.07454
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

The Sweet Danger of Sugar: Debunking Representation Learning for Encrypted Traffic Classification
di: Zhao, Yuqi, et al.
Pubblicazione: (2025)

Wireless Network Digital Twin for 6G: Generative AI as A Key Enabler
di: Tao, Zhenyu, et al.
Pubblicazione: (2023)

Data Augmentation for Traffic Classification
di: Wang, Chao, et al.
Pubblicazione: (2024)

Adaptive Federated Learning in Heterogeneous Wireless Networks with Independent Sampling
di: Geng, Jiaxiang, et al.
Pubblicazione: (2024)

Inference-to-complete: A High-performance and Programmable Data-plane Co-processor for Neural-network-driven Traffic Analysis
di: Wen, Dong, et al.
Pubblicazione: (2024)

TURBOTEST: Learning When Less is Enough through Early Termination of Internet Speed Tests
di: Manda, Haarika, et al.
Pubblicazione: (2025)

NetMamba: Efficient Network Traffic Classification via Pre-training Unidirectional Mamba
di: Wang, Tongze, et al.
Pubblicazione: (2024)

FastFlow: Early Yet Robust Network Flow Classification using the Minimal Number of Time-Series Packets
di: Babaria, Rushi Jayeshkumar, et al.
Pubblicazione: (2025)

A Multi-Agent, Policy-Gradient approach to Network Routing
di: Tao, Nigel, et al.
Pubblicazione: (2025)

Agile Orchestration at Will: An Entire Smart Service-Based Security Architecture Towards 6G
di: Duan, Zhuoran, et al.
Pubblicazione: (2025)

Building Transparency in Deep Learning-Powered Network Traffic Classification: A Traffic-Explainer Framework
di: Ponraj, Riya, et al.
Pubblicazione: (2025)

SwiftChannel: Algorithm-Hardware Co-Design for Deep Learning-Based 5G Channel Estimation
di: Lyu, Shengzhe, et al.
Pubblicazione: (2026)

Energy-Efficient Deep Learning for Traffic Classification on Microcontrollers
di: Chehade, Adel, et al.
Pubblicazione: (2025)

Semi-Decentralized Federated Edge Learning for Fast Convergence on Non-IID Data
di: Sun, Yuchang, et al.
Pubblicazione: (2021)

PLATONT: Learning a Platonic Representation for Unified Network Tomography
di: Du, Chengze, et al.
Pubblicazione: (2025)

Confidence-Regulated Generative Diffusion Models for Reliable AI Agent Migration in Vehicular Metaverses
di: Kang, Yingkai, et al.
Pubblicazione: (2025)

Denoising and Adaptive Online Vertical Federated Learning for Sequential Multi-Sensor Data in Industrial Internet of Things
di: Wang, Heqiang, et al.
Pubblicazione: (2025)

HetCCL: Enabling Collective Communication For Mixed-Vendor Heterogeneous Clusters
di: Wang, Yuejie, et al.
Pubblicazione: (2026)

Practical and Configurable Network Traffic Classification Using Probabilistic Machine Learning
di: Chen, Jiahui, et al.
Pubblicazione: (2021)

MLFCIL: A Multi-Level Forgetting Mitigation Framework for Federated Class-Incremental Learning in LEO Satellites
di: Zhang, Heng, et al.
Pubblicazione: (2026)

Bias in the Shadows: Explore Shortcuts in Encrypted Network Traffic Classification
di: Wang, Chuyi, et al.
Pubblicazione: (2026)

Temporal Hyperbolic Graph Representation Learning for Scale-Free Internet Routing and Delay Prediction
di: Kuo, Yi-Ling, et al.
Pubblicazione: (2026)

NSC-SL: A Bandwidth-Aware Neural Subspace Compression for Communication-Efficient Split Learning
di: Fang, Zhen, et al.
Pubblicazione: (2026)

Causal Intervention Sequence Analysis for Fault Tracking in Radio Access Networks
di: Shi, Chenhua, et al.
Pubblicazione: (2025)

Sequence Spreading-Based Semantic Communication Under High RF Interference
di: Barka, Hazem, et al.
Pubblicazione: (2025)

Universal Embedding Function for Traffic Classification via QUIC Domain Recognition Pretraining: A Transfer Learning Success
di: Luxemburk, Jan, et al.
Pubblicazione: (2025)

PACC: Protocol-Aware Cross-Layer Compression for Compact Network Traffic Representation
di: Guo, Zhaochen, et al.
Pubblicazione: (2026)

FedsLLM: Federated Split Learning for Large Language Models over Communication Networks
di: Zhao, Kai, et al.
Pubblicazione: (2024)

Learning to Optimize Joint Source and RIS-assisted Channel Encoding for Multi-User Semantic Communication Systems
di: Wang, Haidong, et al.
Pubblicazione: (2026)

Early Detection of Network Service Degradation: An Intra-Flow Approach
di: Bicski, Balint, et al.
Pubblicazione: (2024)

Efficient Split Federated Learning for Large Language Models over Communication Networks
di: Zhao, Kai, et al.
Pubblicazione: (2025)

LLM-Driven Stationarity-Aware Expert Demonstrations for Multi-Agent Reinforcement Learning in Mobile Systems
di: Duan, Tianyang, et al.
Pubblicazione: (2025)

Distributed Deep Reinforcement Learning Based Gradient Quantization for Federated Learning Enabled Vehicle Edge Computing
di: Zhang, Cui, et al.
Pubblicazione: (2024)

Socialized Learning: A Survey of the Paradigm Shift for Edge Intelligence in Networked Systems
di: Wang, Xiaofei, et al.
Pubblicazione: (2024)

Q-Learning-Based Time-Critical Data Aggregation Scheduling in IoT
di: Vo, Van-Vi, et al.
Pubblicazione: (2025)

Interpretable Feature Learning in Multivariate Big Data Analysis for Network Monitoring
di: Camacho, José, et al.
Pubblicazione: (2019)

Geminet: Learning the Duality-based Iterative Process for Lightweight Traffic Engineering in Changing Topologies
di: Liu, Ximeng, et al.
Pubblicazione: (2025)

Heterogeneity-Oblivious Robust Federated Learning
di: Zhang, Weiyao, et al.
Pubblicazione: (2025)

LEACH-RLC: Enhancing IoT Data Transmission with Optimized Clustering and Reinforcement Learning
di: Jurado-Lasso, F. Fernando, et al.
Pubblicazione: (2024)

A Deep Reinforcement Learning Framework for Optimizing Congestion Control in Data Centers
di: Ketabi, Shiva, et al.
Pubblicazione: (2023)