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130
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GECCO
2009
Springer
188views Optimization» more  GECCO 2009»
15 years 7 months ago
Exploiting multiple classifier types with active learning
Many approaches to active learning involve training one classifier by periodically choosing new data points about which the classifier has the least confidence, but designing a co...
Zhenyu Lu, Josh Bongard
158
Voted
IGARSS
2009
15 years 1 months ago
Active Learning of Hyperspectral Data with Spatially Dependent Label Acquisition Costs
Supervised learners can be used to automatically classify many types of spatially distributed data. For example, land cover classification by hyperspectral image data analysis is ...
Alexander Liu, Goo Jun, Joydeep Ghosh
125
Voted
AAAI
2006
15 years 5 months ago
Active Learning with Near Misses
Assume that we are trying to build a visual recognizer for a particular class of objects--chairs, for example--using existing induction methods. Assume the assistance of a human t...
Nela Gurevich, Shaul Markovitch, Ehud Rivlin
139
Voted
ICIP
2006
IEEE
16 years 5 months ago
Precision-Oriented Active Selection for Interactive Image Retrieval
Active learning methods have been considered with an increased interest in the content-based image retrieval (CBIR) community. Those methods used to be based on classical classifi...
Philippe Henri Gosselin, Matthieu Cord
119
Voted
NIPS
2007
15 years 5 months ago
Nearest-Neighbor-Based Active Learning for Rare Category Detection
Rare category detection is an open challenge for active learning, especially in the de-novo case (no labeled examples), but of significant practical importance for data mining - ...
Jingrui He, Jaime G. Carbonell