Thesis supervisor: András Horváth
Location of studies (in Hungarian): Pazmany Peter Catholic University, faculty of Information Tecnholgy and Bionics Abbreviation of location of studies: PPKE
Description of the research topic:
"Optimization methods (including convex optimization and gradient based algorithm) became more and more popular. Although these methods enabled the solution of new and new problems, they are computationally extensive and require complex machine with high power consumption.
Because of this it is particularly important to create algorithms which can be efficiently implemented on analogue emerging devices and take into consideration the device characteristics.
The aim of this research is to design and evaluate algorithms and methods, which can be used for solving optimization tasks (e.g.: K-SAT and error minimization in networks) and can be efficiently implemented on low-power emerging devices, are scalable and can be used to solve general problems and problem classes.
"
Required language skills: English Further requirements: user level knowledge of the python programming language, experience optimization problems, good analytical thinking
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