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JMLR
2008
151views more  JMLR 2008»
14 years 10 months ago
Learning to Combine Motor Primitives Via Greedy Additive Regression
The computational complexities arising in motor control can be ameliorated through the use of a library of motor synergies. We present a new model, referred to as the Greedy Addit...
Manu Chhabra, Robert A. Jacobs
FGR
2006
IEEE
121views Biometrics» more  FGR 2006»
15 years 4 months ago
Learning to Identify Facial Expression During Detection Using Markov Decision Process
While there has been a great deal of research in face detection and recognition, there has been very limited work on identifying the expression on a face. Many current face detect...
Ramana Isukapalli, Ahmed M. Elgammal, Russell Grei...
JMLR
2010
121views more  JMLR 2010»
14 years 4 months ago
Sparse Semi-supervised Learning Using Conjugate Functions
In this paper, we propose a general framework for sparse semi-supervised learning, which concerns using a small portion of unlabeled data and a few labeled data to represent targe...
Shiliang Sun, John Shawe-Taylor
NIPS
2001
14 years 11 months ago
Online Learning with Kernels
Abstract--Kernel-based algorithms such as support vector machines have achieved considerable success in various problems in batch setting, where all of the training data is availab...
Jyrki Kivinen, Alex J. Smola, Robert C. Williamson
ICRA
2008
IEEE
137views Robotics» more  ICRA 2008»
15 years 4 months ago
SVM-based discriminative accumulation scheme for place recognition
— Integrating information coming from different sensors is a fundamental capability for autonomous robots. For complex tasks like topological localization, it would be desirable ...
Andrzej Pronobis, Óscar Martínez Moz...