CSDA
2008
13 years 4 months ago
2008
A Bayesian approach to analyze the modes of variation in a set of curves is suggested. It is based on a generative model thus allowing for noisy and sparse observations of curves....
ICML
2010
IEEE
13 years 5 months ago
2010
IEEE
We develop a semi-supervised learning method that constrains the posterior distribution of latent variables under a generative model to satisfy a rich set of feature expectation c...
NIPS
1997
13 years 5 months ago
1997
Up-propagation is an algorithm for inverting and learning neural network generative models. Sensory input is processed by inverting a model that generates patterns from hidden var...
NIPS
2000
13 years 5 months ago
2000
We describe a neurally-inspired, unsupervised learning algorithm that builds a non-linear generative model for pairs of face images from the same individual. Individuals are then ...
NIPS
2000
13 years 5 months ago
2000
Recent work has exploited boundedness of data in the unsupervised learning of new types of generative model. For nonnegative data it was recently shown that the maximum-entropy ge...
ACL
1997
13 years 5 months ago
1997
In this paper we first propose a new statistical parsing model, which is a generative model of lexicalised context-free grammar. We then extend the model to include a probabilisti...
NAACL
2004
13 years 5 months ago
2004
A given entity, representing a person, a location or an organization, may be mentioned in text in multiple, ambiguous ways. Understanding natural language requires identifying whe...
ACL
2004
13 years 6 months ago
2004
This paper describes an incremental parsing approach where parameters are estimated using a variant of the perceptron algorithm. A beam-search algorithm is used during both traini...
AAAI
2004
13 years 6 months ago
2004
A given entity
NIPS
2007
13 years 6 months ago
2007
Estimation of three-dimensional articulated human pose and motion from images is a central problem in computer vision. Much of the previous work has been limited by the use of cru...