576 search results - page 9 / 116 » Structured metric learning for high dimensional problems |
SIAMIS
2010
13 years 2 months ago
2010
We study geometric reconstruction problems in one-dimensional retina vision. In such problems, the scene is modeled as a 2D plane, and the camera sensor produces 1D images of the s...
ICML
2006
IEEE
14 years 8 months ago
2006
IEEE
This paper examines high dimensional regression with noise-contaminated input and output data. Goals of such learning problems include optimal prediction with noiseless query poin...
PREMI
2005
Springer
14 years 1 months ago
2005
Springer
In the typical nonparametric approach to classification in instance-based learning and data mining, random data (the training set of patterns) are collected and used to design a d...
CORR
2012
Springer
12 years 3 months ago
2012
Springer
We study the problem of learning high dimensional regression models regularized by a structured-sparsity-inducing penalty that encodes prior structural information on either input...
COLT
2010
Springer
13 years 5 months ago
2010
Springer
We consider the dimensionality-reduction problem (finding a subspace approximation of observed data) for contaminated data in the high dimensional regime, where the number of obse...