Many classification algorithms use the concept of distance or similarity between patterns. Previous work has shown that it is advantageous to optimize general Euclidean distances (...
We study a generalized framework for structured sparsity. It extends the well known methods of Lasso and Group Lasso by incorporating additional constraints on the variables as pa...
Luca Baldassarre, Jean Morales, Andreas Argyriou, ...
We present an information theoretic perspective on optimal broadband matching. Most of the broadband matching and communication theory literature assumes a frequencyflat reflection...
It is shown that the minimum cut ratio is within a factor of O(log k) of the maximum concurrent flow for k-commodity flow instances with arbitrary capacities and demands. This im...
In this paper a method is presented to fair the limit surface of a subdivision algorithm locally around an extraordinary point. The dominant six eigenvalues of the subdivision mat...