Abstract. We study computationally hard combinatorial problems arising from the important engineering question of how to maximize the number of connections that can be simultaneous...
Abstract. Kernelizations are an important tool in designing fixed parameter algorithms for parameterized decision problems. We introduce an analogous notion for counting problems,...
We consider a MIMO system where error-prone feedback from the receiver is used by the transmitter to select a single optimum antenna to transmit data. Such error-prone feedback is...
Yabo Li, Neelesh B. Mehta, Andreas F. Molisch, Jin...
Vicarious Learning is learning from watching others learn. We believe that this is a powerful model for computer-based learning. Learning episodes can be captured and replayed to ...
Clustering is ill-defined. Unlike supervised learning where labels lead to crisp performance criteria such as accuracy and squared error, clustering quality depends on how the cl...
Rich Caruana, Mohamed Farid Elhawary, Nam Nguyen, ...