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NIPS
2003
13 years 8 months ago
Linear Dependent Dimensionality Reduction
We formulate linear dimensionality reduction as a semi-parametric estimation problem, enabling us to study its asymptotic behavior. We generalize the problem beyond additive Gauss...
Nathan Srebro, Tommi Jaakkola
ICASSP
2011
IEEE
12 years 11 months ago
MIMO radar diversity with Neyman-Pearson signal detection in non-Gaussian circumstance with non-orthogonal waveforms
The diversity gain of a multiple-input multiple-output (MIMO) system adopting the Neyman-Pearson (NP) criterion is derived for a signal-present versus signal-absent scalar hypothe...
Qian He, Rick S. Blum
ICIP
2007
IEEE
14 years 9 months ago
High Dimension Lattice Vector Quantizer Design for Generalized Gaussian Distributions
LVQ is a simple but powerful tool for vector quantization and can be viewed as a vector generalization of uniform scalar quantization. Like VQ, LVQ is able to take into account sp...
Leonardo H. Fonteles, Marc Antonini
ICASSP
2011
IEEE
12 years 11 months ago
Rapid speaker adaptation with speaker adaptive training and non-negative matrix factorization
In this paper, we describe a novel speaker adaptation algorithm based on Gaussian mixture weight adaptation. A small number of latent speaker vectors are estimated with non-negati...
Xueru Zhang, Kris Demuynck, Hugo Van hamme
IJCV
2008
188views more  IJCV 2008»
13 years 7 months ago
Partial Linear Gaussian Models for Tracking in Image Sequences Using Sequential Monte Carlo Methods
The recent development of Sequential Monte Carlo methods (also called particle filters) has enabled the definition of efficient algorithms for tracking applications in image sequen...
Elise Arnaud, Étienne Mémin