1018 search results - page 117 / 204 » Learning Probabilistic Models of Contours |
ICML
2008
IEEE
15 years 10 months ago
2008
IEEE
Sampling is a popular way of scaling up machine learning algorithms to large datasets. The question often is how many samples are needed. Adaptive stopping algorithms monitor the ...
IJCV
2008
14 years 10 months ago
2008
We develop hierarchical, probabilistic models for objects, the parts composing them, and the visual scenes surrounding them. Our approach couples topic models originally developed...
111
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JMLR
2006
14 years 10 months ago
2006
We develop a new component analysis framework, the Noisy-Or Component Analyzer (NOCA), that targets high-dimensional binary data. NOCA is a probabilistic latent variable model tha...
JAIR
2006
14 years 10 months ago
2006
In this paper we propose a data intensive approach for inferring sentence-internal temporal relations. Temporal inference is relevant for practical NLP applications which either e...
140
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CVPR
2009
IEEE
16 years 5 months ago
2009
IEEE
Scarcity and infeasibility of human supervision for large
scale multi-class classification problems necessitates active
learning. Unfortunately, existing active learning methods
...