In this paper, we develop an efficient logistic regression model for multiple instance learning that combines L1 and L2 regularisation techniques. An L1 regularised logistic regr...
Maximum Margin Matrix Factorization (MMMF) was recently suggested (Srebro et al., 2005) as a convex, infinite dimensional alternative to low-rank approximations and standard facto...
L1 regularization is effective for feature selection, but the resulting optimization is challenging due to the non-differentiability of the 1-norm. In this paper we compare state...
We describe a new implementation of the well-known incremental algorithm for constructing Delaunay triangulations in any dimension. Our implementation follows the exact computing ...
Jean-Daniel Boissonnat, Olivier Devillers, Samuel ...
We present a method that computes a global potentially visible set for the complete region outside the convex hull of an object. The technique is used to remove invisible parts (t...