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149
Voted
CVPR
2011
IEEE
14 years 10 months ago
FlowBoost - Appearance Learning from Sparsely Annotated Video
We propose a new learning method which exploits temporal consistency to successfully learn a complex appearance model from a sparsely labeled training video. Our approach consists...
Karim Ali, Francois Fleuret, David Hasler
102
Voted
ICML
2008
IEEE
16 years 3 months ago
Learning for control from multiple demonstrations
We consider the problem of learning to follow a desired trajectory when given a small number of demonstrations from a sub-optimal expert. We present an algorithm that (i) extracts...
Adam Coates, Pieter Abbeel, Andrew Y. Ng
129
Voted
JMLR
2010
136views more  JMLR 2010»
14 years 9 months ago
Reducing Label Complexity by Learning From Bags
We consider a supervised learning setting in which the main cost of learning is the number of training labels and one can obtain a single label for a bag of examples, indicating o...
Sivan Sabato, Nathan Srebro, Naftali Tishby
111
Voted
CVPR
2007
IEEE
16 years 4 months ago
Learning Color Names from Real-World Images
Within a computer vision context color naming is the action of assigning linguistic color labels to image pixels. In general, research on color naming applies the following paradi...
Joost van de Weijer, Cordelia Schmid, Jakob J. Ver...
110
Voted
WWW
2009
ACM
16 years 3 months ago
Towards context-aware search by learning a very large variable length hidden markov model from search logs
Capturing the context of a user's query from the previous queries and clicks in the same session may help understand the user's information need. A context-aware approac...
Huanhuan Cao, Daxin Jiang, Jian Pei, Enhong Chen, ...