The use of Mercer kernel methods in statistical learning theory provides for strong learning capabilities, as seen in kernel principal component analysis and support vector machin...
One of the main shortcomings of Markov chain Monte Carlo samplers is their inability to mix between modes of the target distribution. In this paper we show that advance knowledge ...
In the Weighted Finite State Transducer (WFST) framework for speech recognition, we can reduce memory usage and increase flexibility by using on-the-fly composition which genera...
Tasuku Oonishi, Paul R. Dixon, Koji Iwano, Sadaoki...
Abstract—We address the problem of maximizing the minimum signal to interference and noise ratio of individual users via linear precoding in a multiuser downlink channel with mul...
Albrecht J. Fehske, Fred Richter, Gerhard Fettweis
This paper presents the evolving objects library (EOlib), an object-oriented framework for evolutionary computation (EC) that aims to provide a flexible set of classes to build EC...