We consider the problem of fitting a large-scale covariance matrix to multivariate Gaussian data in such a way that the inverse is sparse, thus providing model selection. Beginnin...
Onureena Banerjee, Laurent El Ghaoui, Alexandre d'...
In this paper we propose an algorithm to estimate missing
values in tensors of visual data. The values can be missing
due to problems in the acquisition process, or because
the ...
Ji Liu, Przemyslaw Musialski, Peter Wonka, Jieping...
Many structured prediction tasks involve complex models where inference is computationally intractable, but where it can be well approximated using a linear programming relaxation...
Ofer Meshi, David Sontag, Tommi Jaakkola, Amir Glo...
We consider a kernel-based approach to nonlinear classification that coordinates the generation of “synthetic” points (to be used in the kernel) with “chunking” (working wi...
Data streaming management and scheduling is required by many grid computing applications, especially when the volume of data to be processed is extremely high while available stor...