Essays about: "monte carlo algorithm"
Showing result 16 - 20 of 165 essays containing the words monte carlo algorithm.
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16. Benchmarking a memetic algorithm for global all-atom protein-protein docking with backbone flexibility
University essay from Lunds universitet/Kemiska institutionenAbstract : Determining how proteins interact with each other to form complexes is very important for understanding both disease and cellular functions, but experimentally determining the structures of these complexes is both tedious and slow, which is why a great number of protein-protein docking algorithms have been developed to predict them. To this day, conformational changes in protein backbones have been one of the largest challenges when making docking predictions. READ MORE
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17. Optimization and Bayesian Modeling of Road Distance for Inventory of Potholes in Gävle Municipality
University essay from Stockholms universitet/Statistiska institutionenAbstract : Time management and distance evaluation have long been a difficult task for workers and companies. This thesis studies 6712 pothole coordinates in Gävle municipality, and evaluates the minimal total road distance needed to visit each pothole once, and return to an initial pothole. READ MORE
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18. Comparison of initialization methods of K-means clustering for small data
University essay from Uppsala universitet/Statistiska institutionenAbstract : Clustering of observations into groups arises as a fundamental challenge both in academia and industry. Many clustering algorithms exist, and the most widely used clustering algorithm, the K-means, notably suffers from sensitivity to initial allocation of cluster centers. READ MORE
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19. Towards Deep Learning Accelerated Sparse Bayesian Frequency Estimation
University essay from Lunds universitet/Matematisk statistikAbstract : The Discrete Fourier Transform is the simplest way to obtain the spectrum of a discrete complex signal. This thesis concerns the case when the signal is known to contain a small (unknown) number of frequencies, not limited to the discrete Fourier frequencies, embedded in complex Gaussian noise. READ MORE
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20. Deep Reinforcement Learning for Card Games
University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)Abstract : This project aims to investigate how reinforcement learning (RL) techniques can be applied to the card game LimitTexas Hold’em. RL is a type of machine learning that can learn to optimally solve problems that can be formulated according toa Markov Decision Process. READ MORE
