Learning problems form an important category of computational tasks that generalizes many of the computations researchers apply to large real-life data sets. We ask: what concept ...
Shiva Prasad Kasiviswanathan, Homin K. Lee, Kobbi ...
In recent years analysis of complexity of learning Gaussian mixture models from sampled data has received significant attention in computational machine learning and theory commun...
We give a simple framework which is an alternative to the celebrated and widely used shifting strategy of Hochbaum and Maass [J. ACM, 1985] which has yielded efficient algorithms ...
This paper introduces a sparse signal representation algorithm in redundant dictionaries, called the M-Term Pursuit (MTP), with an application to image representation and scalable ...
Adel Rahmoune, Pierre Vandergheynst, Pascal Frossa...
Abstract— In this contribution projection approximation subspace tracking using deflation (PASTD) is investigated in the context of MIMO transmit preprocessing systems by exploi...