121 citations
- University of ConnecticutUS4 papers
- Innaxis Foundation & Research InstituteES3 papers
- Korea Institute for Advanced StudyKR3 papers
- Laboratoire de Physique ThéoriqueFR3 papers
- Université Toulouse III - Paul SabatierFR3 papers
- University College LondonGB3 papers
- Calico Life SciencesUS2 papers
- Centre National de la Recherche ScientifiqueFR2 papers
- City, University of LondonGB2 papers
- Deep Blue (Italy)IT2 papers
- Institut de Recherche sur les Systèmes Atomiques et Moléculaires ComplexesFR2 papers
- Laboratoire de Physique Théorique et Modèles StatistiquesFR2 papers
43 papers
A Meta-Heuristic Load Balancer for Cloud Computing Systems
Leszek Sliwko, Vladimir Getov
This paper presents a strategy to allocate services on a Cloud system without overloading nodes and maintaining the system stability with minimum cost. We specify an abstract model…
AGOCS -- Accurate Google Cloud Simulator Framework
Leszek Sliwko, Vladimir Getov
This paper presents the Accurate Google Cloud Simulator (AGOCS) - a novel high-fidelity Cloud workload simulator based on parsing real workload traces, which can be conveniently us…
Enhancing Cluster Scheduling in HPC: A Continuous Transfer Learning for Real-Time Optimization
Leszek Sliwko, Jolanta Mizera-Pietraszko
This study presents a machine learning-assisted approach to optimize task scheduling in cluster systems, focusing on node-affinity constraints. Traditional schedulers like Kubernet…
Cluster Workload Allocation: A Predictive Approach Leveraging Machine Learning Efficiency
Leszek Sliwko
This research investigates how Machine Learning (ML) algorithms can assist in workload allocation strategies by detecting tasks with node affinity operators (referred to as constra…
Policy to Assist Iteratively Local Segmentation: Optimising Modality and Location Selection for Prostate Cancer Localisation
Xiangcen Wu, Shaheer U. Saeed, Yipei Wang +2
Radiologists often mix medical image reading strategies, including inspection of individual modalities and local image regions, using information at different locations from differ…
AI-assisted prostate cancer detection and localisation on biparametric MR by classifying radiologist-positives
Xiangcen Wu, Yipei Wang, Qianye Yang +5
Prostate cancer diagnosis through MR imaging have currently relied on radiologists' interpretation, whilst modern AI-based methods have been developed to detect clinically signific…