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FOIKS
2008
Springer
16 years 1 months ago
Cost-minimising strategies for data labelling : optimal stopping and active learning
Supervised learning deals with the inference of a distribution over an output or label space $\CY$ conditioned on points in an observation space $\CX$, given a training dataset $D$...
Christos Dimitrakakis, Christian Savu-Krohn
CVPR
2011
IEEE
15 years 16 days 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
MASS
2010
15 years 2 months ago
Geography-aware active data dissemination in mobile social networks
Abstract--In mobile social networks (MSNets), data dissemination is an important topic, which has not been widely investigated yet. Active data dissemination is a networking paradi...
Jialu Fan, Yuan Du, Wei Gao, Jiming Chen, Youxian ...
ECCV
2010
Springer
15 years 9 months ago
Detecting People Using Mutually Consistent Poselet Activations
Bourdev and Malik (ICCV 09) introduced a new notion of parts, poselets, constructed to be tightly clustered both in the configuration space of keypoints, as well as in the appeara...
FOIKS
2008
Springer
15 years 6 months ago
Cost-Minimising Strategies for Data Labelling: Optimal Stopping and Active Learning
Supervised learning deals with the inference of a distribution over an output or label space Y conditioned on points in an observation space X , given a training dataset D of pair...
Christos Dimitrakakis, Christian Savu-Krohn