We present a probabilistic approach to learning a Gaussian Process classifier in the presence of unlabeled data. Our approach involves a "null category noise model" (NCN...
Bayesian Regularization and Nonnegative Deconvolution (BRAND) is proposed for estimating time delays of acoustic signals in reverberant environments. Sparsity of the nonnegative f...
This paper presents VLSI circuits with continuous-valued probabilistic behaviour realized by injecting noise into each computing unit(neuron). Interconnecting the noisy neurons fo...
A new method for object search is proposed. The proposed scheme is based on matching gradient information around each pixel, computed in the form of orientation codes, rather than...
We present a decomposition-based approach to managing probabilistic information. We introduce world-set decompositions (WSDs), a space-efficient and complete representation system ...