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» Learning from Multiple Annotators with Gaussian Processes
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ECAI
2004
Springer
14 years 23 days ago
Combining Multiple Answers for Learning Mathematical Structures from Visual Observation
Learning general truths from the observation of simple domains and, further, learning how to use this knowledge are essential capabilities for any intelligent agent to understand ...
Paulo Santos, Derek R. Magee, Anthony G. Cohn, Dav...
ICML
2008
IEEE
14 years 8 months ago
Estimating local optimums in EM algorithm over Gaussian mixture model
EM algorithm is a very popular iteration-based method to estimate the parameters of Gaussian Mixture Model from a large observation set. However, in most cases, EM algorithm is no...
Zhenjie Zhang, Bing Tian Dai, Anthony K. H. Tung
IJCV
2011
264views more  IJCV 2011»
13 years 2 months ago
Cost-Sensitive Active Visual Category Learning
Abstract We present an active learning framework that predicts the tradeoff between the effort and information gain associated with a candidate image annotation, thereby ranking un...
Sudheendra Vijayanarasimhan, Kristen Grauman
BMCBI
2005
134views more  BMCBI 2005»
13 years 7 months ago
Inherited disorder phenotypes: controlled annotation and statistical analysis for knowledge mining from gene lists
Background: Analysis of inherited diseases and their associated phenotypes is of great importance to gain knowledge of underlying genetic interactions and could ultimately give cl...
Marco Masseroli, Osvaldo Galati, Mauro Manzotti, K...
ACL
1996
13 years 8 months ago
Minimizing Manual Annotation Cost in Supervised Training from Corpora
Corpus-based methods for natural language processing often use supervised training, requiring expensive manual annotation of training corpora. This paper investigates methods for ...
Sean P. Engelson, Ido Dagan