Learning Low Density Separators
@article{BenDavid2009LearningLD, title={Learning Low Density Separators}, author={Shai Ben-David and Tyler Lu and D. P{\'a}l and Miroslava Sot{\'a}kov{\'a}}, journal={ArXiv}, year={2009}, volume={abs/0805.2891} }
We define a novel, basic, unsupervised learning problem – learning hyperplane passing through the origin with the lowest probability density. Namely, given a random sample generated by some unknown probability distribution, the task is to find a hyperplane passing through the origin with smallest integral of the probability density on the hyperplane. This task is relevant to several problems in machine learning, such as semisupervised learning and clustering stability. We investigate the… CONTINUE READING
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