236 search results - page 11 / 48 » Learning How to Propagate Using Random Probing |
NIPS
2004
13 years 9 months ago
2004
We seek to both detect and segment objects in images. To exploit both local image data as well as contextual information, we introduce Boosted Random Fields (BRFs), which use boos...
UAI
2004
13 years 9 months ago
2004
Classical learning assumes the learner is given a labeled data sample, from which it learns a model. The field of Active Learning deals with the situation where the learner begins...
ICML
2004
IEEE
14 years 8 months ago
2004
IEEE
Many NLP tasks rely on accurately estimating word dependency probabilities P(w1|w2), where the words w1 and w2 have a particular relationship (such as verb-object). Because of the...
IJCNLP
2005
Springer
14 years 1 months ago
2005
Springer
We present a method of chunking in Korean texts using conditional random fields (CRFs), a recently introduced probabilistic model for labeling and segmenting sequence of data. In a...
IJRR
2007
13 years 7 months ago
2007
Learning patterns of human behavior from sensor data is extremely important for high-level activity inference. We show how to extract a person’s activities and significant plac...