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Showing result 21 - 25 of 92 essays matching the above criteria.
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21. Profitability of Technical Trading Strategies in the Swedish Equity Market
University essay from KTH/Matematisk statistikAbstract : This study aims to see if it is possible to generate abnormal returns in the Swedishstock market through the use of three different trading strategies based on technicalindicators. As the indicators are based on historical price data only, the study assumesweak market efficiency according to the efficient market hypothesis. READ MORE
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22. Can Feebly Interacting Massive Particles (FIMP) constitute Dark Matter?
University essay from KTH/FysikAbstract : In this study, we investigate the feasibility of Feebly Interacting Massive particles (FIMP) as possible candidates to constitute the observed Dark Matter abundance in the universe. FIMPs are particles that couple very feebly with known particles in the Standard Model (SM). READ MORE
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23. Parametrization of a Lithium-ion battery
University essay from KTH/KemiteknikAbstract : Batterimodeller används för att representera batterier. För ändamål som batterihanteringssystem används idag främst empiriska modeller som representerar ett batteri med en motsvarande kretsmodell. Några nackdelar för dessa modeller ligger i dess oförmåga att simulera interna tillstånd och en tidskrävande parametriseringsprocess. READ MORE
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24. International Business Expansion : A guide to decision-making for greenfield expansions
University essay from KTH/Skolan för industriell teknik och management (ITM)Abstract : Globalization has gradually increased exchanges and connections between countries. For companies, globalization entails enhanced opportunity. They embrace a broader set of business possibilities, and leverage resources in foreign countries, by growing their business abroad. READ MORE
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25. Machine Unlearning and hyperparameters optimization in Gaussian Process regression
University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)Abstract : The establishment of the General Data Protection Regulation (GDPR) in Europe in 2018, including the "Right to be Forgotten" poses important questions about the necessity of efficient data deletion techniques for trained Machine Learning models to completely enforce this right, since retraining from scratch such models whenever a data point must be deleted seems impractical. We tackle such a problem for Gaussian Process Regression and define in this paper an efficient exact unlearning technique for Gaussian Process Regression which completely include the optimization of the hyperparameters of the kernel function. READ MORE