Search for dissertations about: "SVMs"
Showing result 1 - 5 of 7 swedish dissertations containing the word SVMs.
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1. From protein sequence to structural instability and disease
Abstract : A great challenge in bioinformatics is to accurately predict protein structure and function from its amino acid sequence, including annotation of protein domains, identification of protein disordered regions and detecting protein stability changes resulting from amino acid mutations. The combination of bioinformatics, genomics and proteomics becomes essential for the investigation of biological, cellular and molecular aspects of disease, and therefore can greatly contribute to the understanding of protein structures and facilitating drug discovery. READ MORE
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2. Distributed and federated learning of support vector machines and applications
Abstract : Machine Learning (ML) has achieved remarkable success in solving classification, regression, and related problems over the past decade. In particular the exponential growth of digital data, makes using ML inevitable and necessary to exploit the wealth of information hidden inside the data. READ MORE
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3. Computational and spatial analyses of rooftops for urban solar energy planning
Abstract : In cities where land availability is limited, rooftop photovoltaic panels (RPVs) offer high potential for satisfying concentrated urban energy demand by using only rooftop areas. However, accurate estimation of RPVs potential in relation to their spatial distribution is indispensable for successful energy planning. READ MORE
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4. High-Performance Computing For Support Vector Machines
Abstract : Machine learning algorithms are very successful in solving classification and regression problems, however the immense amount of data created by digitalization slows down the training and predicting processes, if solvable at all. High-Performance Computing(HPC) and particularly parallel computing are promising tools for improving the performance of machine learning algorithms in terms of time. READ MORE
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5. Visual Representations and Models: From Latent SVM to Deep Learning
Abstract : Two important components of a visual recognition system are representation and model. Both involves the selection and learning of the features that are indicative for recognition and discarding those features that are uninformative. READ MORE