993 search results - page 75 / 199 » Learning RoboCup-Keepaway with Kernels |
212
click to vote
PSIVT
2009
Springer
16 years 8 days ago
2009
Springer
PCA-SIFT is an extension to SIFT which aims to reduce SIFT’s high dimensionality (128 dimensions) by applying PCA to the gradient image patches. However PCA is not a discriminati...
188
click to vote
ICANN
2005
Springer
15 years 11 months ago
2005
Springer
Abstract. Tuning hyper-parameters is a necessary step to improve learning algorithm performances. For Support Vector Machine classifiers, adjusting kernel parameters increases dra...
200
click to vote
JMLR
2010
15 years 16 days ago
2010
We prove the statistical consistency of kernel Partial Least Squares Regression applied to a bounded regression learning problem on a reproducing kernel Hilbert space. Partial Lea...
181
click to vote
ICCV
2009
IEEE
16 years 10 months ago
2009
IEEE
Mean shift clustering is a powerful unsupervised data
analysis technique which does not require prior knowledge
of the number of clusters, and does not constrain the shape
of th...
161
click to vote
ICCV
2009
IEEE
16 years 10 months ago
2009
IEEE
Common visual codebook generation methods used in
a Bag of Visual words model, e.g. k-means or Gaussian
Mixture Model, use the Euclidean distance to cluster features
into visual...