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FLAIRS
2009
15 years 4 months ago
Mining Default Rules from Statistical Data
In this paper, we are interested in the qualitative knowledge that underlies some given probabilistic information. To represent such qualitative structures, we use ordinal conditi...
Gabriele Kern-Isberner, Matthias Thimm, Marc Finth...
INTERSPEECH
2010
15 years 1 months ago
Hierarchical bottle neck features for LVCSR
This paper investigates the combination of different neural network topologies for probabilistic feature extraction. On one hand, a five-layer neural network used in bottle neck f...
Christian Plahl, Ralf Schlüter, Hermann Ney
JMLR
2010
144views more  JMLR 2010»
15 years 1 months ago
Practical Approaches to Principal Component Analysis in the Presence of Missing Values
Principal component analysis (PCA) is a classical data analysis technique that finds linear transformations of data that retain the maximal amount of variance. We study a case whe...
Alexander Ilin, Tapani Raiko
ICASSP
2011
IEEE
14 years 10 months ago
A general Bayesian algorithm for visual object tracking based on sparse features
This paper describes a Bayesian algorithm for rigid/non-rigid 2D visual object tracking based on sparse image features. The algorithm is inspired by the way human visual cortex se...
Mauricio Soto Alvarez, Carlo S. Regazzoni
DCC
2005
IEEE
16 years 5 months ago
Real, Tight Frames with Maximal Robustness to Erasures
Motivated by the use of frames for robust transmission over the Internet, we present a first systematic construction of real tight frames with maximum robustness to erasures. We a...
Jelena Kovacevic, Markus Püschel