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» Using Machine Learning to Focus Iterative Optimization
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ICML
2003
IEEE
16 years 3 months ago
The Cross Entropy Method for Fast Policy Search
We present a learning framework for Markovian decision processes that is based on optimization in the policy space. Instead of using relatively slow gradient-based optimization al...
Shie Mannor, Reuven Y. Rubinstein, Yohai Gat
NN
2007
Springer
106views Neural Networks» more  NN 2007»
15 years 2 months ago
Machine learning approach to color constancy
A number of machine learning (ML) techniques have recently been proposed to solve color constancy problem in computer vision. Neural networks (NNs) and support vector regression (...
Vivek Agarwal, Andrei V. Gribok, Mongi A. Abidi
TNN
2010
159views Management» more  TNN 2010»
14 years 9 months ago
Multiple incremental decremental learning of support vector machines
We propose a multiple incremental decremental algorithm of Support Vector Machine (SVM). Conventional single incremental decremental SVM can update the trained model efficiently w...
Masayuki Karasuyama, Ichiro Takeuchi
150
Voted
CORR
2008
Springer
193views Education» more  CORR 2008»
15 years 2 months ago
Faster and better: a machine learning approach to corner detection
The repeatability and efficiency of a corner detector determines how likely it is to be useful in a real-world application. The repeatability is importand because the same scene vi...
Edward Rosten, Reid Porter, Tom Drummond
105
Voted
ICML
2006
IEEE
16 years 3 months ago
Classifying EEG for brain-computer interfaces: learning optimal filters for dynamical system features
Classification of multichannel EEG recordings during motor imagination has been exploited successfully for brain-computer interfaces (BCI). In this paper, we consider EEG signals ...
Le Song, Julien Epps