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Sotirios T. Spantideas
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2020 – today
- 2024
- [c12]Ilias Paralikas
, Sotiris T. Spantideas
Lightweight Inference by Neural Network Pruning: Accuracy, Time and Comparison. AIAI (3) 2024: 248-257 - [c11]Marios Christopoulos
Deep Reinforcement Learning for Smart Home Temperature Comfort in IoT-Edge Computing Systems. MECC@EuroSys 2024 - 2023
- [c10]Anastasios E. Giannopoulos, Sotirios T. Spantideas, Nikolaos Nomikos, Alexandros Kalafatelis
Learning to Fulfill the User Demands in 5G-enabled Wireless Networks through Power Allocation: a Reinforcement Learning approach. DRCN 2023: 1-7 - [c9]Sotirios T. Spantideas, Anastasios E. Giannopoulos, Marta Amor Cambeiro, Óscar Trullols-Cruces, Eneko Atxutegi, Panagiotis Trakadas:
Intelligent Mission Critical Services over Beyond 5G Networks: Control Loop and Proactive Overload Detection. SmartNets 2023: 1-6 - 2022
- [j5]Anastasios E. Giannopoulos
Supporting Intelligence in Disaggregated Open Radio Access Networks: Architectural Principles, AI/ML Workflow, and Use Cases. IEEE Access 10: 39580-39595 (2022) - [j4]Panagiotis Trakadas
A Reference Architecture for Cloud-Edge Meta-Operating Systems Enabling Cross-Domain, Data-Intensive, ML-Assisted Applications: Architectural Overview and Key Concepts. Sensors 22(22): 9003 (2022) - [c8]Theofanis Karamplias, Sotirios T. Spantideas, Anastasios E. Giannopoulos
Towards Closed-loop Automation in 5G Open RAN: Coupling an Open-Source Simulator with xApps. EuCNC 2022: 232-237 - [c7]Sotirios T. Spantideas, Anastasios E. Giannopoulos, Nikolaos C. Kapsalis, Angelos Angelopoulos, Stamatis Voliotis, Panagiotis Trakadas:
Towards Zero-Defect Manufacturing: Machine Selection through Unsupervised Learning in the Printing Industry. I-ESA Workshops 2022 - [c6]Angelos Angelopoulos
Allocating Orders to Printing Machines for Defect Minimization: A Comparative Machine Learning Approach. AIAI (2) 2022: 79-88 - 2021
- [j3]Anastasios E. Giannopoulos, Sotirios T. Spantideas, Nikolaos C. Kapsalis, Panagiotis Karkazis, Panagiotis Trakadas:
Deep Reinforcement Learning for Energy-Efficient Multi-Channel Transmissions in 5G Cognitive HetNets: Centralized, Decentralized and Transfer Learning Based Solutions. IEEE Access 9: 129358-129374 (2021) - [j2]Panagiotis Trakadas, Lambros Sarakis, Anastasios E. Giannopoulos, Sotirios T. Spantideas, Nikolaos Capsalis, Panagiotis K. Gkonis, Panagiotis Karkazis, Giovanni Rigazzi, Angelos Antonopoulos, Marta Amor Cambeiro, Sergio Gonzalez-Diaz, Luís Conceição:
A Cost-Efficient 5G Non-Public Network Architectural Approach: Key Concepts and Enablers, Building Blocks and Potential Use Cases. Sensors 21(16): 5578 (2021) - [c5]Angelos Angelopoulos
Impact of Classifiers to Drift Detection Method: A Comparison. EANN 2021: 399-410 - [c4]Alexandros Kalafatelis
ISLAND: An Interlinked Semantically-Enriched Blockchain Data Framework. GECON 2021: 207-214 - [c3]Anastasios E. Giannopoulos
Power Control in 5G Heterogeneous Cells Considering User Demands Using Deep Reinforcement Learning. AIAI Workshops 2021: 95-105 - [c2]Sotirios T. Spantideas, Anastasios E. Giannopoulos
Joint Energy-efficient and Throughput-sufficient Transmissions in 5G Cells with Deep Q-Learning. MeditCom 2021: 265-270 - [c1]Anastasios E. Giannopoulos, Sotirios T. Spantideas, Nikolaos Capsalis, Panagiotis K. Gkonis, Panos Karkazis, Lambros Sarakis, Panos Trakadas, Christos N. Capsalis:
WIP: Demand-Driven Power Allocation in Wireless Networks with Deep Q-Learning. WOWMOM 2021: 248-251
2010 – 2019
- 2018
- [j1]Vassilis P. Kalogirou, Adrianos G. Katsouris
A Reorganization Method for Existing DTT Networks in View of the Second Digital Dividend Implementation: The Greek Example. Wirel. Pers. Commun. 98(1): 439-451 (2018)
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aka: Panos Trakadas
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