The importance estimation problem (estimating the ratio of two probability density functions) has recently gathered a great deal of attention for use in various applications, e.g....
Amplitude demodulation is an ill-posed problem and so it is natural to treat it from a Bayesian viewpoint, inferring the most likely carrier and envelope under probabilistic const...
Data sparseness is an ever dominating problem in automatic emotion recognition. Using artificially generated speech for training or adapting models could potentially ease this: t...
— We are currently witnessing an increasing interest in the use of the web as an information and knowledge source. Much of the information sought after in the web is in this case...
Heiko Stoermer, Themis Palpanas, George Giannakopo...
The ensemble Kalman filter for data assimilation involves the propagation of a collection of ensemble members. Under the assumption of time-sparse measurements, we avoid propagatin...