We propose a novel algorithm for clustering data sampled from multiple submanifolds of a Riemannian manifold. First, we learn a representation of the data using generalizations of...
We present similarity-based methods to cluster digital photos by time and image content. The approach is general, unsupervised, and makes minimal assumptions regarding the structu...
Matthew L. Cooper, Jonathan Foote, Andreas Girgens...
We use a combination of proven methods from time series analysis and machine learning to explore the relationship between temporal and semantic similarity in web query logs; we di...
Bing Liu 0003, Rosie Jones, Kristina Lisa Klinkner
A new distance measure between probability density functions (pdfs) is introduced, which we refer to as the Laplacian pdf distance. The Laplacian pdf distance exhibits a remarkabl...
In previous work on "transformed mixtures of Gaussians" and "transformed hidden Markov models", we showed how the EM algorithm in a discrete latent variable mo...