Essays about: "Distributed algorithm"
Showing result 1 - 5 of 232 essays containing the words Distributed algorithm.
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1. Blockchain-based e-voting system without digital ID: A Proof-of-Concept
University essay from Karlstads universitet/Institutionen för matematik och datavetenskap (from 2013)Abstract : Electronic voting systems have the potential to offer a cost effective, secure and transparent way of communicating with the citizens, increasing trust and participation. However creating a secure open source electronic voting system providing confidentiality and transparency with sufficient performance has long been a challenge. READ MORE
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2. DISTRIBUTED ARTIFICIAL INTELLIGENCE FOR ANOMALY DETECTION IN A MODULAR MANUFACTURING ENVIRONMENT
University essay from Mälardalens universitet/Akademin för innovation, design och teknikAbstract : This thesis investigates anomaly detection and classification in a simulated modular manufacturingenvironment using Machine Learning algorithm Random Forest. This algorithm is tested on a localcomputer and an embedded device, specifically the Raspberry PI. READ MORE
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3. Control perspective on distributed optimization
University essay from Uppsala universitet/Sannolikhetsteori och kombinatorikAbstract : In the intersection between machine learning, artificial intelligence and mathe- matical computation lies optimization. A powerful tool that enables us to solve a variety of large scale problems. The purpose of this work is to explore optimiza- tion in the distributed setting. READ MORE
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4. Artificial Transactional Data Generation for Benchmarking Algorithms
University essay from Umeå universitet/Institutionen för fysikAbstract : Modern retailers have been collecting more and more data over the past decades. The increased sizes of collected data have led to higher demand for data analytics expertise tools, which the Umeå-founded company Infobaleen provides. A recurring challenge when developing such tools is the data itself. READ MORE
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5. Over-the-Air Federated Learning with Compressed Sensing
University essay from Linköpings universitet/KommunikationssystemAbstract : The rapid progress with machine learning (ML) technology has solved previously unsolved problems, but training these ML models requires ever larger datasets and increasing amounts of computational resources. One potential solution is to enable parallelization of the computations and allow local processing of training data in distributed nodes, such as Federated Learning (FL). READ MORE