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» Selectivity Estimation using Probabilistic Models
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CORR
2007
Springer
128views Education» more  CORR 2007»
14 years 11 months ago
Model Selection Through Sparse Maximum Likelihood Estimation
We consider the problem of estimating the parameters of a Gaussian or binary distribution in such a way that the resulting undirected graphical model is sparse. Our approach is to...
Onureena Banerjee, Laurent El Ghaoui, Alexandre d'...
NIPS
2000
15 years 1 months ago
Speech Denoising and Dereverberation Using Probabilistic Models
This paper presents a unified probabilistic framework for denoising and dereverberation of speech signals. The framework transforms the denoising and dereverberation problems into...
Hagai Attias, John C. Platt, Alex Acero, Li Deng
ICAI
2009
14 years 9 months ago
The Utility of Affect in the Selection of Actions and Goals Under Real-World Constraints
We present a novel affective goal selection mechanism for decision-making in agents with limited computational resources (e.g., such as robots operating under real-time constraint...
Paul W. Schermerhorn, Matthias Scheutz
CORR
2004
Springer
108views Education» more  CORR 2004»
14 years 11 months ago
Efficiency Enhancement of Probabilistic Model Building Genetic Algorithms
Abstract. This paper presents two different efficiency-enhancement techniques for probabilistic model building genetic algorithms. The first technique proposes the use of a mutatio...
Kumara Sastry, David E. Goldberg, Martin Pelikan
ICC
2007
IEEE
104views Communications» more  ICC 2007»
15 years 3 months ago
Self-Interference Suppression in Doubly-Selective Channel Estimation Using Superimposed Training
Abstract-- Channel estimation for frequency-selective timevarying channels is considered using superimposed training. We employ a discrete prolate spheroidal basis expansion model ...
Shuangchi He, Jitendra K. Tugnait