Výsledky vyhledávání

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SplitLLM: Collaborative Inference of LLMs for Model Placement and Throughput Optimization

Autor: Mudvari, Akrit, Jiang, Yuang, Tassiulas, Leandros

Large language models (LLMs) have been a disruptive innovation in recent years, and they play a crucial role in our daily lives due to their ability to understand and generate human-like text. Their capabilities include natural language understanding

Externí odkaz: http://arxiv.org/abs/2410.10759

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Compiler for Distributed Quantum Computing: a Reinforcement Learning Approach

Autor: Promponas, Panagiotis, Mudvari, Akrit, Della Chiesa, Luca, Polakos, Paul, Samuel, Louis, Tassiulas, Leandros

The practical realization of quantum programs that require large-scale qubit systems is hindered by current technological limitations. Distributed Quantum Computing (DQC) presents a viable path to scalability by interconnecting multiple Quantum Proce

Externí odkaz: http://arxiv.org/abs/2404.17077

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Predictive Handover Strategy in 6G and Beyond: A Deep and Transfer Learning Approach

Autor: Panitsas, Ioannis, Mudvari, Akrit, Maatouk, Ali, Tassiulas, Leandros

Next-generation cellular networks will evolve into more complex and virtualized systems, employing machine learning for enhanced optimization and leveraging higher frequency bands and denser deployments to meet varied service demands. This evolution,

Externí odkaz: http://arxiv.org/abs/2404.08113

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Constrained Reinforcement Learning for Adaptive Controller Synchronization in Distributed SDN

Autor: Panitsas, Ioannis, Mudvari, Akrit, Tassiulas, Leandros

In software-defined networking (SDN), the implementation of distributed SDN controllers, with each controller responsible for managing a specific sub-network or domain, plays a critical role in achieving a balance between centralized control, scalabi

Externí odkaz: http://arxiv.org/abs/2403.08775

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Joint SDN Synchronization and Controller Placement in Wireless Networks using Deep Reinforcement Learning

Autor: Mudvari, Akrit, Tassiulas, Leandros

Software Defined Networking has afforded numerous benefits to the network users but there are certain persisting issues with this technology, two of which are scalability and privacy. The natural solution to overcoming these limitations is a distribu

Externí odkaz: http://arxiv.org/abs/2311.05582

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Adaptive Compression-Aware Split Learning and Inference for Enhanced Network Efficiency

Autor: Mudvari, Akrit, Vainio, Antero, Ofeidis, Iason, Tarkoma, Sasu, Tassiulas, Leandros

The growing number of AI-driven applications in mobile devices has led to solutions that integrate deep learning models with the available edge-cloud resources. Due to multiple benefits such as reduction in on-device energy consumption, improved late

Externí odkaz: http://arxiv.org/abs/2311.05739

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Akademický článek

Academic performance and musculoskeletal pain in adolescents with uncorrected vision problems

Autor: Hanne-Mari Schiøtz Thorud, Prabeen Raj Mudvari, Helle K. Falkenberg

Publikováno v: BMC Pediatrics, Vol 24, Iss 1, Pp 1-9 (2024)

Abstract Background Undetected vision problems are common in school children, and a prevalence of up to 40% has previously been reported. Uncorrected vision and lack of optimal eye wear can have a significant impact on almost all aspects of everyday

Externí odkaz: https://doaj.org/article/936f68c042ac43bf8aa380bee4c6dff1

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Akademický článek

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