24 search results - page 2 / 5 » Learning nonparametric kernel matrices from pairwise constra... |
ICCV
2009
IEEE
14 years 9 months ago
2009
IEEE
Clustering performance can often be greatly improved by
leveraging side information. In this paper, we consider constrained
clustering with pairwise constraints, which specify
s...
NIPS
2004
13 years 6 months ago
2004
We present a novel method for learning with Gaussian process regression in a hierarchical Bayesian framework. In a first step, kernel matrices on a fixed set of input points are l...
ICDCS
2007
IEEE
13 years 11 months ago
2007
IEEE
Learning the underlying model from distributed data is often useful for many distributed systems. In this paper, we study the problem of learning a non-parametric model from distr...
CVPR
2010
IEEE
13 years 2 months ago
2010
IEEE
Pictorial structure (PS) models are extensively used for part-based recognition of scenes, people, animals and multi-part objects. To achieve tractability, the structure and param...
ICML
2010
IEEE
13 years 5 months ago
2010
IEEE
We study the problem of uncertainty in the entries of the Kernel matrix, arising in SVM formulation. Using Chance Constraint Programming and a novel large deviation inequality we ...