Search for dissertations about: "c# and big data"
Showing result 1 - 5 of 23 swedish dissertations containing the words c# and big data.
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1. Explainable and Resource-Efficient Stream Processing Through Provenance and Scheduling
Abstract : In our era of big data, information is captured at unprecedented volumes and velocities, with technologies such as Cyber-Physical Systems making quick decisions based on the processing of streaming, unbounded datasets. In such scenarios, it can be beneficial to process the data in an online manner, using the stream processing paradigm implemented by Stream Processing Engines (SPEs). READ MORE
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2. Clustering in the Big Data Era: methods for efficient approximation, distribution, and parallelization
Abstract : Data clustering is an unsupervised machine learning task whose objective is to group together similar items. As a versatile data mining tool, data clustering has numerous applications, such as object detection and localization using data from 3D laser-based sensors, finding popular routes using geolocation data, and finding similar patterns of electricity consumption using smart meters. READ MORE
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3. Efficient Approximate Big Data Clustering: Distributed and Parallel Algorithms in the Spectrum of IoT Architectures
Abstract : Clustering, the task of grouping together similar items, is a frequently used method for processing data, with numerous applications. Clustering the data generated by sensors in the Internet of Things, for instance, can be useful for monitoring and making control decisions. READ MORE
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4. Privacy-guardian : the vital need in machine learning with big data
Abstract : Social Network Sites (SNS) such as Facebook and Twitter, play a great role in our lives. On one hand, they help to connect people who would not otherwise be connected. Many recent breakthroughs in AI such as facial recognition [Kow+18], were achieved thanks to the amount of available data on the Internet via SNS (hereafter Big Data). READ MORE
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5. Asynchronous First-Order Algorithms for Large-Scale Optimization : Analysis and Implementation
Abstract : Developments in communication and data storage technologies have made large-scale data collection more accessible than ever. The transformation of this data into insight or decisions typically involves solving numerical optimization problems. READ MORE