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» Robust Boosting for Learning from Few Examples
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SIGGRAPH
2010
ACM
15 years 2 months ago
Learning behavior styles with inverse reinforcement learning
We present a method for inferring the behavior styles of character controllers from a small set of examples. We show that a rich set of behavior variations can be captured by dete...
Seong Jae Lee, Zoran Popovic
AAAI
2011
13 years 9 months ago
Quantity Makes Quality: Learning with Partial Views
In many real world applications, the number of examples to learn from is plentiful, but we can only obtain limited information on each individual example. We study the possibiliti...
Nicolò Cesa-Bianchi, Shai Shalev-Shwartz, O...
CVPR
2010
IEEE
15 years 3 months ago
Multi-Target Tracking by On-Line Learned Discriminative Appearance Models
We present an approach for online learning of discriminative appearance models for robust multi-target tracking in a crowded scene from a single camera. Although much progress has...
Cheng-Hao Kuo, Chang Huang, Ram Nevatia
FOCS
2009
IEEE
15 years 4 months ago
A Complete Characterization of Statistical Query Learning with Applications to Evolvability
Statistical query (SQ) learning model of Kearns is a natural restriction of the PAC learning model in which a learning algorithm is allowed to obtain estimates of statistical prop...
Vitaly Feldman
ICCV
2009
IEEE
1019views Computer Vision» more  ICCV 2009»
16 years 2 months ago
Similarity Functions for Categorization: from Monolithic to Category Specific
Similarity metrics that are learned from labeled training data can be advantageous in terms of performance and/or efficiency. These learned metrics can then be used in conjuncti...
Boris Babenko, Steve Branson, Serge Belongie