We show that if the closureof a function class F under the metric induced by some probability distribution is not convex, then the sample complexity for agnostically learning F wi...
Wee Sun Lee, Peter L. Bartlett, Robert C. Williams...
Abstract. We present two data-driven importance distributions for particle filterbased articulated tracking; one based on background subtraction, another on depth information. In ...
Simulated tempering (ST) is an established Markov Chain Monte Carlo (MCMC) methodology for sampling from a multimodal density π(θ). The technique involves introducing an auxilia...
Abstract. This paper argues for the benefits of distinguishing the notions of “ontology module” and “importing terms from an ontology”, by sampling some papers on these to...
Background: Advances in DNA microarray technology portend that molecular signatures from which microarray will eventually be used in clinical environments and personalized medicin...
Zhenqiang Su, Huixiao Hong, Hong Fang, Leming M. S...