This paper addresses the problem of segmenting a combination of linear subspaces and quadratic surfaces from sample data points corrupted by (not necessarily small) noise. Our mai...
Necmiye Ozay, Mario Sznaier, Constantino M. Lagoa,...
We use convex relaxation techniques to produce lower bounds on the optimal value of subset selection problems and generate good approximate solutions. We then explicitly bound the...
Francis Bach, Selin Damla Ahipasaoglu, Alexandre d...
We propose an unsupervised image segmentation method based on texton similarity and mode seeking. The input image is first convolved with a filter-bank, followed by soft cluster...
Let F be a compact subset of the n-dimensional Euclidean space Rn represented by (finitely or infinitely many) quadratic inequalities. We propose two methods, one based on successi...
We present a method for designing operational amplifiers using reversed geometric programming, which is an extension of geometric programming that allows both convex and non-conve...