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» Structural Learning of Activities from Sparse Datasets
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EMNLP
2004
13 years 10 months ago
Active Learning and the Total Cost of Annotation
Active learning (AL) promises to reduce the cost of annotating labeled datasets for trainable human language technologies. Contrary to expectations, when creating labeled training...
Jason Baldridge, Miles Osborne
MTA
2006
173views more  MTA 2006»
13 years 8 months ago
Active learning in very large databases
Abstract. Query-by-example and query-by-keyword both suffer from the problem of "aliasing," meaning that example-images and keywords potentially have variable interpretat...
Navneet Panda, Kingshy Goh, Edward Y. Chang
BMCBI
2010
172views more  BMCBI 2010»
13 years 3 months ago
Nonparametric identification of regulatory interactions from spatial and temporal gene expression data
Background: The correlation between the expression levels of transcription factors and their target genes can be used to infer interactions within animal regulatory networks, but ...
Anil Aswani, Soile V. E. Keränen, James Brown...
PKDD
2010
Springer
158views Data Mining» more  PKDD 2010»
13 years 7 months ago
Learning Sparse Gaussian Markov Networks Using a Greedy Coordinate Ascent Approach
In this paper, we introduce a simple but efficient greedy algorithm, called SINCO, for the Sparse INverse COvariance selection problem, which is equivalent to learning a sparse Ga...
Katya Scheinberg, Irina Rish
IUI
2006
ACM
14 years 2 months ago
Interactive learning of structural shape descriptions from automatically generated near-miss examples
Sketch interfaces provide more natural interaction than the traditional mouse and palette tool, but can be time consuming to build if they have to be built anew for each new domai...
Tracy Hammond, Randall Davis