Browsing Theses by Subject "Kernel Methods"
Now showing items 1-4 of 4
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Effective and Efficient Optimization Methods for Kernel Based Classification Problems
(University of Waterloo, 2014-04-22)Kernel methods are a popular choice in solving a number of problems in statistical machine learning. In this thesis, we propose new methods for two important kernel based classification problems: 1) learning from highly ... -
Exemplar-based Kernel Preserving Embedding
(University of Waterloo, 2016-05-02)With the rapid increase of available data, it becomes computationally harder to extract useful information, specially in the case of high-dimensional data. Choosing a representative subset of the data can be useful to ... -
The Power Landmark Vector Learning Framework
(University of Waterloo, 2008-05-12)Kernel methods have recently become popular in bioinformatics machine learning. Kernel methods allow linear algorithms to be applied to non-linear learning situations. By using kernels, non-linear learning problems can ... -
Scalable Embeddings for Kernel Clustering on MapReduce
(University of Waterloo, 2014-02-18)There is an increasing demand from businesses and industries to make the best use of their data. Clustering is a powerful tool for discovering natural groupings in data. The k-means algorithm is the most commonly-used data ...