24 search results - page 1 / 5 » Projection Penalties: Dimension Reduction without Loss |
ICML
2010
IEEE
13 years 5 months ago
2010
IEEE
Dimension reduction is popular for learning predictive models in high-dimensional spaces. It can highlight the relevant part of the feature space and avoid the curse of dimensiona...
SODA
2012
ACM
11 years 7 months ago
2012
ACM
Statistical data frequently includes outliers; these can distort the results of estimation procedures and optimization problems. For this reason, loss functions which deemphasize ...
TSMC
2010
12 years 11 months ago
2010
We study the problem of projecting high-dimensional tensor data on an unspecified Riemannian manifold onto some lower dimensional subspace1 without much distorting the pairwise geo...
ICB
2009
Springer
13 years 11 months ago
2009
Springer
The small sample size problem and the difficulty in determining the optimal reduced dimension limit the application of subspace learning methods in the gait recognition domain. To...
ISCAS
2007
IEEE
13 years 11 months ago
2007
IEEE
Process variation in future technologies can cause severe performance degradation since different parts of the shared Register File (RF) in VLIW processors may operate at various ...