534 search results - page 43 / 107 » Model Uncertainty in Classical Conditioning |
ICASSP
2009
IEEE
14 years 2 months ago
2009
IEEE
Model compensation schemes are a powerful approach to handling mismatches between training and testing conditions. Normally these schemes are run in a batch adaptation mode, re-re...
FOCS
2005
IEEE
14 years 1 months ago
2005
IEEE
Stochastic optimization problems provide a means to model uncertainty in the input data where the uncertainty is modeled by a probability distribution over the possible realizatio...
DAGSTUHL
2007
13 years 9 months ago
2007
Stochastic optimization problems provide a means to model uncertainty in the input data where the uncertainty is modeled by a probability distribution over the possible realizatio...
ICPR
2010
IEEE
14 years 1 months ago
2010
IEEE
Abstract—Due to their ability to model sequential data without making unnecessary independence assumptions, conditional random fields (CRFs) have become an increasingly popular ...
ICPR
2006
IEEE
14 years 9 months ago
2006
IEEE
This paper integrates Markov random fields (MRFs) with type-2 fuzzy sets (T2 FSs) referred to as T2 FMRFs, which can handle the fuzziness of the labeling space as well as the rand...