We propose a framework which we call stochastic offline programming (SOP). The idea is to embed the development of combinatorial algorithms in an off-line learning environment whi...
Maximum likelihood estimators are often of limited practical use due to the intensive computation they require. We propose a family of alternative estimators that maximize a stoch...
Recently, there is an increasing interest in the deployment of femto access points (FAPs), which are short-range low-power home basestations, over a macro cellular network to impr...
Wang Chi Cheung, Tony Q. S. Quek, Marios Kountouri...
To accelerate the training of kernel machines, we propose to map the input data to a randomized low-dimensional feature space and then apply existing fast linear methods. The feat...