We consider embeddings of structures which preserve spectra: if g : M → S with S computable, then M should have the same Turing degree spectrum (as a structure) that g(M) has (a...
This paper describes BoostMap, a method for efficient nearest neighbor retrieval under computationally expensive distance measures. Database and query objects are embedded into a v...
Vassilis Athitsos, Jonathan Alon, Stan Sclaroff, G...
This paper presents an improved analysis of a structured dimension-reduction map called the subsampled randomized Hadamard transform. This argument demonstrates that the map preser...
Locally Linear Embedding (LLE) has recently been proposed as a method for dimensional reduction of high-dimensional nonlinear data sets. In LLE each data point is reconstructed fro...
Claudio Varini, Andreas Degenhard, Tim W. Nattkemp...
Manifold learning methods are promising data analysis tools. However, if we locate a new test sample on the manifold, we have to find its embedding by making use of the learned e...