49 search results - page 4 / 10 » Learning Multi-category Classification in Bayesian Framework |
PAMI
2006
13 years 5 months ago
2006
Gaussian process classifiers (GPCs) are Bayesian probabilistic kernel classifiers. In GPCs, the probability of belonging to a certain class at an input location is monotonically re...
CVPR
1999
IEEE
14 years 7 months ago
1999
IEEE
We present a novel mixed-state dynamic Bayesian network (DBN) framework for modeling and classifying timeseries data such as object trajectories. A hidden Markov model (HMM) of di...
ML
2002
ACM
13 years 5 months ago
2002
ACM
I describe a framework for interpreting Support Vector Machines (SVMs) as maximum a posteriori (MAP) solutions to inference problems with Gaussian Process priors. This probabilisti...
JCIT
2010
13 years 17 days ago
2010
Probability theory is the framework for making decision under uncertainty. In classification, Bayes' rule is used to calculate the probabilities of the classes and it is a bi...
ICIP
2010
IEEE
13 years 3 months ago
2010
IEEE
Most approaches to learn classifiers for structured objects (e.g., images) use generative models in a classical Bayesian framework. However, state-of-the-art classifiers for vecto...