35 search results - page 4 / 7 » Online Multiple Instance Learning with No Regret |
ECCV
2010
Springer
13 years 7 months ago
2010
Springer
Abstract. Multiple-instance learning (MIL) allows for training classifiers from ambiguously labeled data. In computer vision, this learning paradigm has been recently used in many ...
ISVC
2010
Springer
13 years 6 months ago
2010
Springer
Abstract. We propose a novel Multiple Instance Learning (MIL) framework to perform target localization from image sequences. The proposed approach consists of a softmax logistic re...
CVPR
2009
IEEE
15 years 2 months ago
2009
IEEE
The computer aided diagnosis (CAD) problems of detecting
potentially diseased structures from medical images are
typically distinguished by the following challenging characterist...
PODC
2009
ACM
14 years 8 months ago
2009
ACM
We analyze the performance of protocols for load balancing in distributed systems based on no-regret algorithms from online learning theory. These protocols treat load balancing a...
CORR
2011
Springer
12 years 11 months ago
2011
Springer
Learning theory has largely focused on two main learning scenarios. The first is the classical statistical setting where instances are drawn i.i.d. from a fixed distribution and...