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COLT
2010
Springer
13 years 8 months ago
Optimal Algorithms for Online Convex Optimization with Multi-Point Bandit Feedback
Bandit convex optimization is a special case of online convex optimization with partial information. In this setting, a player attempts to minimize a sequence of adversarially gen...
Alekh Agarwal, Ofer Dekel, Lin Xiao
WWW
2005
ACM
14 years 10 months ago
Gimme' the context: context-driven automatic semantic annotation with C-PANKOW
Without the proliferation of formal semantic annotations, the Semantic Web is certainly doomed to failure. In earlier work we presented a new paradigm to avoid this: the 'Sel...
Günter Ladwig, Philipp Cimiano, Steffen Staab
ICCV
2003
IEEE
14 years 12 months ago
A Sparse Probabilistic Learning Algorithm for Real-Time Tracking
This paper addresses the problem of applying powerful pattern recognition algorithms based on kernels to efficient visual tracking. Recently Avidan [1] has shown that object recog...
Oliver M. C. Williams, Andrew Blake, Roberto Cipol...
TROB
2010
159views more  TROB 2010»
13 years 4 months ago
Task-Specific Generalization of Discrete and Periodic Dynamic Movement Primitives
Abstract--Acquisition of new sensorimotor knowledge by imitation is a promising paradigm for robot learning. To be effective, action learning should not be limited to direct replic...
Ales Ude, Andrej Gams, Tamim Asfour, Jun Morimoto
KDD
2002
ACM
171views Data Mining» more  KDD 2002»
14 years 10 months ago
Mining complex models from arbitrarily large databases in constant time
In this paper we propose a scaling-up method that is applicable to essentially any induction algorithm based on discrete search. The result of applying the method to an algorithm ...
Geoff Hulten, Pedro Domingos