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ECML
2001
Springer
14 years 1 months ago
Learning of Variability for Invariant Statistical Pattern Recognition
In many applications, modelling techniques are necessary which take into account the inherent variability of given data. In this paper, we present an approach to model class speciļ...
Daniel Keysers, Wolfgang Macherey, Jörg Dahme...
CORR
2012
Springer
170views Education» more  CORR 2012»
12 years 4 months ago
What Cannot be Learned with Bethe Approximations
We address the problem of learning the parameters in graphical models when inference is intractable. A common strategy in this case is to replace the partition function with its B...
Uri Heinemann, Amir Globerson
SIGIR
2003
ACM
14 years 2 months ago
Text categorization by boosting automatically extracted concepts
Term-based representations of documents have found widespread use in information retrieval. However, one of the main shortcomings of such methods is that they largely disregard le...
Lijuan Cai, Thomas Hofmann
CVPR
2012
IEEE
11 years 11 months ago
Robust visual tracking using autoregressive hidden Markov Model
Recent studies on visual tracking have shown signiļ¬cant improvement in accuracy by handling the appearance variations of the target object. Whereas most studies present schemes ...
Dong Woo Park, Junseok Kwon, Kyoung Mu Lee
GECCO
2005
Springer
156views Optimization» more  GECCO 2005»
14 years 2 months ago
Extraction of informative genes from microarray data
Identiļ¬cation of those genes that might anticipate the clinical behavior of diļ¬€erent types of cancers is challenging due to availability of a smaller number of patient samples...
Topon Kumar Paul, Hitoshi Iba