Essays about: "Bayesianskt ramverk"
Found 4 essays containing the words Bayesianskt ramverk.
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1. The integration of contextual priors and kinematic information during anticipation in skilled boxers : The role of video analysis
University essay from Högskolan i Halmstad/Akademin för hälsa och välfärdAbstract : The current study examined how repetitive exposure of an opponent’s stroke preferences on video affected the integration of contextual priors and kinematic information during anticipation in skilled boxers. We performed an experimental ingroup-design with a temporal-occlusion video-based anticipation task with repeated measures where 19 male skilled boxers (M = 22. READ MORE
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2. An Empirical Evaluation of Context Aware Clustering of Bandits using Thompson Sampling
University essay from KTH/Skolan för datavetenskap och kommunikation (CSC)Abstract : Stochastic bandit algorithms are increasingly being used in the domain of recommender systems, when the environment is very dynamic and the items to recommend are frequently changing over time. While traditional approaches consider a single bandit instance which assumes all users to be equal, recent developments in the literature showed that the quality of recommendations can be improved when individual bandit instances for different users are considered and clustering techniques are used. READ MORE
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3. Bayesian Neural Networks for Short Term Wind Power Forecasting
University essay from KTH/Skolan för datavetenskap och kommunikation (CSC)Abstract : In recent years, wind and other variable renewable energy sources have gained a rapidly increasing share of the global energy mix. In this context the greatest concern facing renewable energy sources like wind is the uncertainty in production volumes as their generation ability is inherently dependent on weather conditions. READ MORE
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4. Small Cohort Population Forecasting via Bayesian Learning
University essay from KTH/Matematisk statistikAbstract : A set of distributional assumptions regarding the demographic processes of birth, death, emigration and immigration have been assembled to form a probabilistic model framework of population dynamics. This framework was summarized as a Bayesian network and Bayesian inference techniques are exploited to infer the posterior distributions of the model parameters from observed data. READ MORE
