Our problem of interest consists of minimizing a separable, convex and differentiable function over a convex set, defined by bounds on the variables and an explicit constraint des...
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 present a novel search algorithm which is suitable for optimizing functions with a high-dimensional discrete-valued parameter vector. The algorithm is designed to find a funct...
Tuukka Toivonen, Loren Merritt, Ville Ojansivu, Ja...
We propose a new notion of secure multiparty computation aided by a computationally-powerful but untrusted “cloud” server. In this notion that we call on-the-fly multiparty c...
A new algorithm is proposed for performing unsupervised tissue classification in medical images by integrating conventional clustering techniques with edge-adaptive segmentation t...