889 search results - page 102 / 178 » Probabilistic Neural Network Models for Sequential Data |
ICML
2000
IEEE
14 years 8 months ago
2000
IEEE
Hidden Markov models (HMMs) are a powerful probabilistic tool for modeling sequential data, and have been applied with success to many text-related tasks, such as part-of-speech t...
CVPR
2007
IEEE
14 years 10 months ago
2007
IEEE
We study the challenging problem of maneuvering object tracking with unknown dynamics, i.e., forces or torque. We investigate the underlying causes of object kinematics, and propo...
NIPS
2008
13 years 9 months ago
2008
Uncertainty is omnipresent when we perceive or interact with our environment, and the Bayesian framework provides computational methods for dealing with it. Mathematical models fo...
ICANN
2009
Springer
14 years 20 days ago
2009
Springer
This paper proposes a modelling of Support Vector Machine (SVM) learning to address the problem of learning with sloppy labels. In binary classification, learning with sloppy labe...
ICANN
2005
Springer
14 years 1 months ago
2005
Springer
This paper presents a new connectionist model of the grounding of linguistic quantifiers in perception that takes into consideration the contextual factors affecting the use of vag...