922 search results - page 110 / 185 » Learning Gaussian Process Models from Uncertain Data |
138
Voted
ICASSP
2011
IEEE
14 years 6 months ago
2011
IEEE
We propose a kernelized maximal-figure-of-merit (MFoM) learning approach to efficiently training a nonlinear model using subspace distance minimization. In particular, a fixed,...
147
Voted
CVPR
2008
IEEE
16 years 4 months ago
2008
IEEE
Graphical models such as Bayesian Networks (BNs) are being increasingly applied to various computer vision problems. One bottleneck in using BN is that learning the BN model param...
169
Voted
JMLR
2012
13 years 5 months ago
2012
While determining model complexity is an important problem in machine learning, many feature learning algorithms rely on cross-validation to choose an optimal number of features, ...
135
Voted
ASC
2008
15 years 2 months ago
2008
Most data mining algorithms assume static behavior of the incoming data. In the real world, the situation is different and most continuously collected data streams are generated by...
141
Voted
CVPR
2012
IEEE
13 years 5 months ago
2012
IEEE
We describe an online approach to learn non-linear motion patterns and robust appearance models for multi-target tracking in a tracklet association framework. Unlike most previous...