In this work a new adaptive fast variational sparse Bayesian learning (V-SBL) algorithm is proposed that is a variational counterpart of the fast marginal likelihood maximization ...
Dmitriy Shutin, Thomas Buchgraber, Sanjeev R. Kulk...
In this work a new online learning algorithm that uses automatic relevance determination (ARD) is proposed for fast adaptive nonlinear filtering. A sequential decision rule for i...
Thomas Buchgraber, Dmitriy Shutin, H. Vincent Poor
The problem of audio source separation from a monophonic sound mixture having known instrument types but unknown timbres is presented. An improvement to the Probabilistic Latent C...
We consider the task of acoustic system identification, where the input signal undergoes a memoryless nonlinear transformation before convolving with an unknown linear system. We...
Non-negative Matrix Factorization (NMF) has found use in single channel separation of audio signals, as it gives a parts-based decomposition of audio spectrograms where the parts ...
Rajesh Jaiswal, Derry Fitzgerald, Dan Barry, Eugen...
In recent years nonpolynomial finite element methods have received increasing attention for the efficient solution of wave problems. As with their close cousin the method of parti...
—Information about the spectral reflectance of a color surface is useful in many applications. Assuming that reflectance functions can be adequately approximated by a linear comb...
We present a computational, group-theoretic approach to steerable functions. The approach is group-theoretic in that the treatment involves continuous transformation groups for wh...
Matching Pursuit algorithms learn a function that is a weighted sum of basis functions, by sequentially appending functions to an initially empty basis, to approximate a target fu...
We apply independent component analysis (ICA) for extracting an optimal basis to the problem of finding efficient features for a speaker. The basis functions learned by the algori...