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» Using Machine Learning to Focus Iterative Optimization
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112
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ALT
2008
Springer
15 years 11 months ago
Active Learning in Multi-armed Bandits
In this paper we consider the problem of actively learning the mean values of distributions associated with a finite number of options (arms). The algorithms can select which opti...
András Antos, Varun Grover, Csaba Szepesv&a...
107
Voted
CVPR
2010
IEEE
15 years 11 months ago
Far-Sighted Active Learning on a Budget for Image and Video Recognition
Active learning methods aim to select the most informative unlabeled instances to label first, and can help to focus image or video annotations on the examples that will most impr...
Sudheendra Vijayanarasimhan, Prateek Jain, Kristen...
118
Voted
ICPR
2010
IEEE
15 years 5 months ago
Fast Training of Object Detection Using Stochastic Gradient Descent
Training datasets for object detection problems are typically very large and Support Vector Machine (SVM) implementations are computationally complex. As opposed to these complex ...
Rob Wijnhoven, Peter H. N. De With
98
Voted
ICALT
2008
IEEE
15 years 9 months ago
Students' Tracking Data: An Approach for Efficiently Tracking Computer Mediated Communications in Distance Learning
This paper presents an approach for closely observing the different levels of Human and Computer Interactions during student’s communication activities on Computer Mediated Comm...
Madeth May, Sébastien George, Patrick Pr&ea...
133
Voted
AAAI
2012
13 years 5 months ago
Model Learning and Real-Time Tracking Using Multi-Resolution Surfel Maps
For interaction with its environment, a robot is required to learn models of objects and to perceive these models in the livestreams from its sensors. In this paper, we propose a ...
Jörg Stückler, Sven Behnke