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CVPR
2011
IEEE
15 years 3 months ago
Large-Scale Live Active Learning: Training Object Detectors with Crawled Data and Crowds
Active learning and crowdsourcing are promising ways to efficiently build up training sets for object recognition, but thus far techniques are tested in artificially controlled ...
Sudheendra Vijayanarasimhan, Kristen Grauman
ESOP
2011
Springer
14 years 10 months ago
Measure Transformer Semantics for Bayesian Machine Learning
Abstract. The Bayesian approach to machine learning amounts to inferring posterior distributions of random variables from a probabilistic model of how the variables are related (th...
Johannes Borgström, Andrew D. Gordon, Michael...
IUI
2011
ACM
14 years 9 months ago
TellMe: learning procedures from tutorial instruction
This paper describes an approach to allow end users to define new procedures through tutorial instruction. Our approach allows users to specify procedures in natural language in t...
Yolanda Gil, Varun Ratnakar, Christian Fritz
ACL
2012
13 years 9 months ago
Exploiting Social Information in Grounded Language Learning via Grammatical Reduction
This paper uses an unsupervised model of grounded language acquisition to study the role that social cues play in language acquisition. The input to the model consists of (orthogr...
Mark Johnson, Katherine Demuth, Michael C. Frank
CVPR
2003
IEEE
16 years 8 months ago
Learning Appearance and Transparency Manifolds of Occluded Objects in Layers
By mapping a set of input images to points in a lowdimensional manifold or subspace, it is possible to efficiently account for a small number of degrees of freedom. For example, i...
Brendan J. Frey, Nebojsa Jojic, Anitha Kannan