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» Learning large margin classifiers locally and globally
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ICRA
2008
IEEE
134views Robotics» more  ICRA 2008»
14 years 2 months ago
Real-time learning of resolved velocity control on a Mitsubishi PA-10
Abstract— Learning inverse kinematics has long been fascinating the robot learning community. While humans acquire this transformation to complicated tool spaces with ease, it is...
Jan Peters, Duy Nguyen-Tuong
TSP
2010
13 years 2 months ago
Testing stationarity with surrogates: a time-frequency approach
An operational framework is developed for testing stationarity relatively to an observation scale, in both stochastic and deterministic contexts. The proposed method is based on a ...
Pierre Borgnat, Patrick Flandrin, Paul Honeine, C&...
ML
2000
ACM
13 years 7 months ago
Maximizing Theory Accuracy Through Selective Reinterpretation
Existing methods for exploiting awed domain theories depend on the use of a su ciently large set of training examples for diagnosing and repairing aws in the theory. In this paper,...
Shlomo Argamon-Engelson, Moshe Koppel, Hillel Walt...
FGR
2000
IEEE
147views Biometrics» more  FGR 2000»
14 years 2 days ago
Hallucinating Faces
In this paper, we study face hallucination or synthesizing a high-resolution face image from a low-resolution input, with the help of a large collection of other highresolution fa...
Simon Baker, Takeo Kanade
TIP
2008
154views more  TIP 2008»
13 years 7 months ago
Adaptive Local Linear Regression With Application to Printer Color Management
Abstract--Local learning methods, such as local linear regression and nearest neighbor classifiers, base estimates on nearby training samples, neighbors. Usually, the number of nei...
Maya R. Gupta, Eric K. Garcia, E. Chin