In this paper we present a novel approach for the 3D Euclidean reconstruction of deformable objects observed by a perspective camera with variable intrinsic parameters. We formula...
Alessio Del Bue, Lourdes de Agapito, Xavier Llad&o...
Optimising the parameters of ranking functions with respect to standard IR rank-dependent cost functions has eluded satisfactory analytical treatment. We build on recent advances ...
Michael J. Taylor, Hugo Zaragoza, Nick Craswell, S...
Bayesian network models are widely used for discriminative prediction tasks such as classification. Usually their parameters are determined using 'unsupervised' methods ...
Background: Our goal is to develop a state-of-the-art protein secondary structure predictor, with an intuitive and biophysically-motivated energy model. We treat structure predict...
Blaise Gassend, Charles W. O'Donnell, William Thie...
The purpose of this paper is to present some numerical tools which facilitate the interpretation of simulation or data fitting results and which allow to compute optimal experimen...