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» Using a Non-prior Training Active Feature Model
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EMNLP
2006
14 years 10 months ago
Better Informed Training of Latent Syntactic Features
We study unsupervised methods for learning refinements of the nonterminals in a treebank. Following Matsuzaki et al. (2005) and Prescher (2005), we may for example split NP withou...
Markus Dreyer, Jason Eisner
109
Voted
LREC
2008
140views Education» more  LREC 2008»
14 years 11 months ago
Toward Active Learning in Data Selection: Automatic Discovery of Language Features During Elicitation
Data Selection has emerged as a common issue in language technologies. We define Data Selection as the choosing of a subset of training data that is most effective for a given tas...
Jonathan Clark, Robert E. Frederking, Lori S. Levi...
PR
2008
328views more  PR 2008»
14 years 9 months ago
Activity based surveillance video content modelling
This paper tackles the problem of surveillance video content modelling. Given a set of surveillance videos, the aims of our work are twofold: firstly a continuous video is segment...
Tao Xiang, Shaogang Gong
ICASSP
2011
IEEE
14 years 1 months ago
Fall detection in a smart room by using a fuzzy one class support vector machine and imperfect training data
In this paper, we propose an efficient and robust fall detection system by using a fuzzy one class support vector machine based on video information. Two cameras are used to capt...
Miao Yu, Syed Mohsen Naqvi, Adel Rhuma, Jonathon A...
ICDM
2006
IEEE
183views Data Mining» more  ICDM 2006»
15 years 3 months ago
Accelerating Newton Optimization for Log-Linear Models through Feature Redundancy
— Log-linear models are widely used for labeling feature vectors and graphical models, typically to estimate robust conditional distributions in presence of a large number of pot...
Arpit Mathur, Soumen Chakrabarti