Empirical divergence maximization is an estimation method similar to empirical risk minimization whereby the Kullback-Leibler divergence is maximized over a class of functions tha...
Linear discriminant analysis (LDA) is a widely used feature extraction method for classification. We introduce distributed implementations of different versions of LDA, suitable ...
Sergio Valcarcel Macua, Pavle Belanovic, Santiago ...
In this paper, we develop a new approach to the robust beamforming for general-rank signal models. Our method is based on the worst-case performance optimization using a semi-de n...
Detecting pitch values for singing voice in the presence of music accompaniment is challenging but useful for many applications. We propose a trend estimation algorithm to detect ...
We propose a novel utterance comparison model based on probability theory and factor analysis that computes the likelihood of two speech utterances originating from the same speak...
This paper presents a detailed sum rate investigation of Zero-Forcing (ZF) detectors over composite multiple-input multiple-output (MIMO) channels. To this end, we consider the ge...
Michail Matthaiou, Nestor D. Chatzidiamantis, Geor...
The 2- 1 sparse signal minimization problem can be solved efficiently by gradient projection. In many applications, the signal to be estimated is known to lie in some range of va...
James Hernandez, Zachary T. Harmany, Daniel Thomps...
This paper considers the problem of extending the single antenna power measurements based direction finding to the two-dimensional (2D) case, and proposes a method to estimate th...
—In this contribution we provide a thorough stability analysis of gradient type algorithms with non-symmetric matrix step-sizes. We hereby extend existing analyses for symmetric ...
We propose a new statistical model, named Hierarchical Topic Trajectory Model (HTTM), for acquiring a dynamically changing topic model that represents the relationship between vid...