Cover Image

FMLFS: A Federated Multi-Label Feature Selection Based on Information Theory in IoT Environment

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Mahanipour, Afsaneh, Khamfroush, Hana
Format:	Preprint
Published:	2024
Subjects:	Machine Learning Information Theory Networking and Internet Architecture
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Semi-Supervised Federated Multi-Label Feature Selection with Fuzzy Information Measures
by: Mahanipour, Afsaneh, et al.
Published: (2025)

Enhancing IoT Security: A Novel Feature Engineering Approach for ML-Based Intrusion Detection Systems
by: Mahanipour, Afsaneh, et al.
Published: (2024)

Embedded Federated Feature Selection with Dynamic Sparse Training: Balancing Accuracy-Cost Tradeoffs
by: Mahanipour, Afsaneh, et al.
Published: (2025)

Joint Energy and Latency Optimization in Federated Learning over Cell-Free Massive MIMO Networks
by: Mahmoudi, Afsaneh, et al.
Published: (2024)

Causal Model-Based Reinforcement Learning for Sample-Efficient IoT Channel Access
by: Arun, Aswin, et al.
Published: (2025)

Smart Pilot Assignment for IoT in Massive MIMO Systems: A Path Towards Scalable IoT Infrastructure
by: Saeed, Muhammad Kamran, et al.
Published: (2024)

Information-Geometric Barycenters for Bayesian Federated Learning
by: Jamoussi, Nour, et al.
Published: (2024)

Optimizing Information Freshness in IoT Systems with Update Rate Constraints: A Token-Based Approach
by: Delfani, Erfan, et al.
Published: (2024)

Client Selection Strategies for Federated Semantic Communications in Heterogeneous IoT Networks
by: Lahoud, Samer, et al.
Published: (2025)

Cost-Free Personalization via Information-Geometric Projection in Bayesian Federated Learning
by: Jamoussi, Nour, et al.
Published: (2025)

Federated Learning in Satellite Constellations
by: Matthiesen, Bho, et al.
Published: (2022)

Optimizing Version AoI in Energy-Harvesting IoT: Model-Based and Learning-Based Approaches
by: Delfani, Erfan, et al.
Published: (2025)

Information Entropy-Based Scheduling for Communication-Efficient Decentralized Learning
by: Nagar, Jaiprakash, et al.
Published: (2025)

Adaptive Federated Learning Over the Air
by: Wang, Chenhao, et al.
Published: (2024)

FedMeld: A Model-dispersal Federated Learning Framework for Space-ground Integrated Networks
by: Chen, Qian, et al.
Published: (2024)

Federated Hyperdimensional Computing for Resource-Constrained Industrial IoT
by: Zeulin, Nikita, et al.
Published: (2026)

Rethinking Clustered Federated Learning in NOMA Enhanced Wireless Networks
by: Lin, Yushen, et al.
Published: (2024)

Data-oriented Coordinated Uplink Transmission for Massive IoT System
by: Hämäläinen, Jyri, et al.
Published: (2024)

Golden Modulation: a New and Effective Waveform for Massive IoT
by: Vangelista, Lorenzo, et al.
Published: (2023)

UAV-assisted Unbiased Hierarchical Federated Learning: Performance and Convergence Analysis
by: Zhagypar, Ruslan, et al.
Published: (2024)

Digital versus Analog Transmissions for Federated Learning over Wireless Networks
by: Yao, Jiacheng, et al.
Published: (2024)

DRACO: Decentralized Asynchronous Federated Learning over Row-Stochastic Wireless Networks
by: Jeong, Eunjeong, et al.
Published: (2024)

Data Similarity-Based One-Shot Clustering for Multi-Task Hierarchical Federated Learning
by: Ali, Abdulmoneam, et al.
Published: (2024)

From AoI to QVAoI: Query-Based Semantics-Aware Scheduling for Energy-Harvesting IoT Systems
by: Delfani, Erfan, et al.
Published: (2024)

Policy Gradient Algorithms for Age-of-Information Cost Minimization
by: Vidal, José-Ramón, et al.
Published: (2025)

Mitigating Pilot Contamination and Enabling IoT Scalability in Massive MIMO Systems
by: Saeed, Muhammad Kamran, et al.
Published: (2023)

State-Aware Timeliness in Energy Harvesting IoT Systems Monitoring a Markovian Source
by: Delfani, Erfan, et al.
Published: (2024)

Timely Information Updating for Mobile Devices Without and With ML Advice
by: Hsu, Yu-Pin, et al.
Published: (2025)

Asynchronous Risk-Aware Multi-Agent Packet Routing for Ultra-Dense LEO Satellite Networks
by: He, Ke, et al.
Published: (2025)

The Best Time for an Update: Risk-Sensitive Minimization of Age-Based Metrics
by: de Sombre, Wanja, et al.
Published: (2024)

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

An Autoencoder-Based Constellation Design for AirComp in Wireless Federated Learning
by: Mu, Yujia, et al.
Published: (2024)

Modeling and Performance Analysis of IoT-over-LEO Satellite Systems under Realistic Operational Constraints: A Stochastic Geometry Approach
by: Dong, Wen-Yu, et al.
Published: (2025)

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

Deep Learning in Wireless Communication Receiver: A Survey
by: Doha, Shadman Rahman, et al.
Published: (2025)

Science-Informed Design of Deep Learning With Applications to Wireless Systems: A Tutorial
by: Termehchi, Atefeh, et al.
Published: (2024)

Lightweight Intrusion Detection in IoT via SHAP-Guided Feature Pruning and Knowledge-Distilled Kronecker Networks
by: Benaddi, Hafsa, et al.
Published: (2025)

Latency-Distortion Tradeoffs in Communicating Classification Results over Noisy Channels
by: Teku, Noel, et al.
Published: (2024)

Deep Joint Source-Channel Coding for Efficient and Reliable Cross-Technology Communication
by: Yao, Shumin, et al.
Published: (2024)

GRLinQ: An Intelligent Spectrum Sharing Mechanism for Device-to-Device Communications with Graph Reinforcement Learning
by: Shan, Zhiwei, et al.
Published: (2024)