We provide a principle for semi-supervised learning based on optimizing the rate of communicating labels for unlabeled points with side information. The side information is expres...
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...
A crucial step toward the goal of automatic extraction of propositional information from natural language text is the identification of semantic relations between constituents in ...
In this paper, we present a complete computational pipeline for extracting a compact shape descriptor for curve point cloud data. Our shape descriptor, called a barcode, is based ...
Anne D. Collins, Afra Zomorodian, Gunnar Carlsson,...
This work reduces the computational requirements of the additive noise steganalysis presented by Harmsen and Pearlman. The additive noise model assumes that the stegoimage is crea...
Jeremiah J. Harmsen, Kevin D. Bowers, William A. P...