We study an extension of the "standard" learning models to settings where observing the value of an attribute has an associated cost (which might be different for differ...
We propose a new approach to recover epipolar geometry from a pair of uncalibrated images. By minimizing a proposed cost function, our approach matches the detected feature points...
Extreme losses of portfolios with heavy-tailed components are studied in the framework of multivariate regular variation. Asymptotic distributions of extreme portfolio losses are ...
We present a framework for designing fast and monotonic algorithms for transmission tomography penalizedlikelihood image reconstruction. The new algorithms are based on paraboloid...
When the goal is to achieve the best correct classification rate, cross entropy and mean squared error are typical cost functions used to optimize classifier performance. However,...
Lian Yan, Robert H. Dodier, Michael Mozer, Richard...