We address a new learning problem where the goal is to build a predictive model that minimizes prediction time (the time taken to make a prediction) subject to a constraint on mod...
Biswanath Panda, Mirek Riedewald, Johannes Gehrke,...
Finite mixture model is a powerful tool in many statistical learning problems. In this paper, we propose a general, structure-preserving approach to reduce its model complexity, w...
We present the implementation and evaluation of a penalized alternating minimization (AM) method1 for the computation of a specimen's complex transmittance function (magnitud...
Restoring binary images is a problem which arises in various application fields. In our paper, this problem is considered in a variational framework: the sought-after solution min...
Discovery of functionaldependencies from relations has been identified as an important database analysis technique. In this paper, we present a new approach for finding functional...