44 search results - page 3 / 9 » Sparse and shift-invariant feature extraction from non-negat... |
NIPS
2007
13 years 7 months ago
2007
Unsupervised learning algorithms aim to discover the structure hidden in the data, and to learn representations that are more suitable as input to a supervised machine than the ra...
ICRA
2006
IEEE
13 years 11 months ago
2006
IEEE
— Most work on the simultaneous localization and mapping (SLAM) problem assumes the frequent availability of dense information about the environment such as that provided by a la...
ICML
2010
IEEE
13 years 6 months ago
2010
IEEE
In Sparse Coding (SC), input vectors are reconstructed using a sparse linear combination of basis vectors. SC has become a popular method for extracting features from data. For a ...
ICASSP
2011
IEEE
12 years 9 months ago
2011
IEEE
The Common Spatial Pattern (CSP) method is a powerful technique for feature extraction from multichannel neural activity and widely used in brain computer interface (BCI) applicat...
PKDD
2001
Springer
13 years 10 months ago
2001
Springer
In some domains, Information Extraction (IE) from texts requires syntactic and semantic parsing. This analysis is computationally expensive and IE is potentially noisy if it applie...