The idea of learning overcomplete dictionaries based on the paradigm of compressive sensing has found numerous applications, among which image denoising is considered one of the m...
Sparsity in the eigenspace of signal covariance matrices is exploited in this paper for compression and denoising. Dimensionality reduction (DR) and quantization modules present i...
Long-span language models that capture syntax and semantics are seldom used in the first pass of large vocabulary continuous speech recognition systems due to the prohibitive sea...
Anoop Deoras, Tomas Mikolov, Stefan Kombrink, Mart...
In this paper, we propose an acceleration technique of the adaptive filtering scheme called adaptive proximal forward-backward splitting method. For accelerating the convergence ...
Abstract—The paper is concerned with a multiuser communication network, which is assisted by multiple relays. It has been observed through our previous related works that the con...