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Skip to Search Results- 2Parameter selection
- 1Clustering parameter
- 1Locality sensitive hashing
- 1Loop closure detection
- 1Nearest neighbor search
- 1Semi-supervised clustering
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Fall 2013
Many clustering techniques require parameter settings and depending on an algorithms sensitivity to the parameter, the choice of the parameter value can be very important. Several approaches have been proposed to find the “best” value of the clustering parameter for the different unsupervised...
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Spring 2012
My thesis focuses on automatic parameter selection for euclidean distance version of Locality Sensitive Hashing (LSH) and solving visual loop closure detection by using LSH. LSH is a class of functions for probabilistic nearest neighbor search. Although some work has been done for parameter...