889 search results - page 10 / 178 » Observational Learning in Random Networks |
ICASSP
2010
IEEE
13 years 8 months ago
2010
IEEE
This paper addresses the problem of state estimation in the case where the prior distribution of the states is not perfectly known but instead is parameterized by some unknown par...
ICML
2009
IEEE
14 years 10 months ago
2009
IEEE
We propose a new neural network architecture, called Simple Recurrent Temporal-Difference Networks (SR-TDNs), that learns to predict future observations in partially observable en...
CVPR
2009
IEEE
15 years 4 months ago
2009
IEEE
Many perception and multimedia indexing problems involve datasets that are naturally comprised of multiple streams or modalities for which supervised training data is only sparsely...
TSD
2010
Springer
13 years 7 months ago
2010
Springer
The main idea of a priori machine learning is to apply a machine learning method on a machine learning problem itself. We call it "a priori" because the processed data se...
ICDM
2005
IEEE
14 years 3 months ago
2005
IEEE
An outlier is an observation that deviates so much from other observations as to arouse suspicion that it was generated by a different mechanism. Outlier detection has many applic...