Markov networks are extensively used to model complex sequential, spatial, and relational interactions in fields as diverse as image processing, natural language analysis, and bio...
Benjamin Taskar, Vassil Chatalbashev, Daphne Kolle...
We consider approximation algorithms for buy-at-bulk network design, with the additional constraint that demand pairs be protected against edge or node failures in the network. In...
Spyridon Antonakopoulos, Chandra Chekuri, F. Bruce...
We study the edge-connectivity survivable network design problem with an additional linear budget constraint. We give a strongly polynomial time (3, 3)-approximation algorithm for ...
Abstract. Using radial basis function networks for function approximation tasks suffers from unavailable knowledge about an adequate network size. In this work, a measuring techni...
- In this paper we investigate mixture of experts problems in the context of Local-Global Neural Networks. This type of architecture was originaly conceived for functional approxim...