Current statistical machine translation systems usually extract rules from bilingual corpora annotated with 1-best alignments. They are prone to learn noisy rules due to alignment...
Learning the underlying model from distributed data is often useful for many distributed systems. In this paper, we study the problem of learning a non-parametric model from distr...
Quantization-based watermarking schemes are vulnerable to amplitude scaling. Therefore the scaling factor has to be accounted for either at the encoder, or at the decoder, prior t...
Ivo D. Shterev, Reginald L. Lagendijk, Richard Heu...
—MapReduce has emerged as a popular tool for distributed and scalable processing of massive data sets and is increasingly being used in e-science applications. Unfortunately, the...
Benjamin Gufler, Nikolaus Augsten, Angelika Reiser...
Most of recent and important algorithms in signal processing (for blind identification or separation, etc) are based on higher order statistics (HOS). And most of them use a crite...