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COLT
1991
Springer
13 years 12 months ago
On the Complexity of Teaching
While most theoretical work in machine learning has focused on the complexity of learning, recently there has been increasing interest in formally studying the complexity of teach...
Sally A. Goldman, Michael J. Kearns
SOFSEM
2010
Springer
14 years 5 months ago
Regret Minimization and Job Scheduling
Regret minimization has proven to be a very powerful tool in both computational learning theory and online algorithms. Regret minimization algorithms can guarantee, for a single de...
Yishay Mansour
ICML
2009
IEEE
14 years 9 months ago
Efficient learning algorithms for changing environments
We study online learning in an oblivious changing environment. The standard measure of regret bounds the difference between the cost of the online learner and the best decision in...
Elad Hazan, C. Seshadhri
CVPR
2007
IEEE
14 years 10 months ago
Learning Features for Tracking
We treat tracking as a matching problem of detected keypoints between successive frames. The novelty of this paper is to learn classifier-based keypoint descriptions allowing to i...
Michael Grabner, Helmut Grabner, Horst Bischof
KDD
2009
ACM
178views Data Mining» more  KDD 2009»
14 years 8 months ago
Catching the drift: learning broad matches from clickthrough data
Identifying similar keywords, known as broad matches, is an important task in online advertising that has become a standard feature on all major keyword advertising platforms. Eff...
Sonal Gupta, Mikhail Bilenko, Matthew Richardson