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NIPS
2008
13 years 9 months ago
Supervised Dictionary Learning
It is now well established that sparse signal models are well suited for restoration tasks and can be effectively learned from audio, image, and video data. Recent research has be...
Julien Mairal, Francis Bach, Jean Ponce, Guillermo...
ICANN
2010
Springer
13 years 7 months ago
Computational Properties of Probabilistic Neural Networks
We discuss the problem of overfitting of probabilistic neural networks in the framework of statistical pattern recognition. The probabilistic approach to neural networks provides a...
Jiri Grim, Jan Hora
COMPUTING
2004
80views more  COMPUTING 2004»
13 years 7 months ago
An Efficient Multigrid Solver based on Distributive Smoothing for Poroelasticity Equations
In this paper, we present a robust distributive smoother in a multigrid method for the system of poroelasticity equations. Within the distributive framework, we deal with a decoup...
R. Wienands, Francisco J. Gaspar, Francisco J. Lis...
SIAMNUM
2010
140views more  SIAMNUM 2010»
13 years 2 months ago
Finite Element Approximation of the Linear Stochastic Wave Equation with Additive Noise
Semidiscrete finite element approximation of the linear stochastic wave equation with additive noise is studied in a semigroup framework. Optimal error estimates for the determinis...
Mihály Kovács, Stig Larsson, Fardin ...
BMVC
2010
13 years 5 months ago
StyP-Boost: A Bilinear Boosting Algorithm for Learning Style-Parameterized Classifiers
We introduce a novel bilinear boosting algorithm, which extends the multi-class boosting framework of JointBoost to optimize a bilinear objective function. This allows style param...
Jonathan Warrell, Philip H. S. Torr, Simon Prince