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» Machine-Learning Applications of Algorithmic Randomness
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NIPS
2004
13 years 11 months ago
Brain Inspired Reinforcement Learning
Successful application of reinforcement learning algorithms often involves considerable hand-crafting of the necessary non-linear features to reduce the complexity of the value fu...
François Rivest, Yoshua Bengio, John Kalask...
ACCV
2009
Springer
14 years 4 months ago
Levels of Details for Gaussian Mixture Models
Mixtures of Gaussians are a crucial statistical modeling tool at the heart of many challenging applications in computer vision and machine learning. In this paper, we first descri...
Vincent Garcia, Frank Nielsen, Richard Nock
GECCO
2007
Springer
194views Optimization» more  GECCO 2007»
14 years 3 months ago
Hybrid coevolutionary algorithms vs. SVM algorithms
As a learning method support vector machine is regarded as one of the best classifiers with a strong mathematical foundation. On the other hand, evolutionary computational techniq...
Rui Li, Bir Bhanu, Krzysztof Krawiec
CCR
2006
136views more  CCR 2006»
13 years 9 months ago
Traffic classification on the fly
The early detection of applications associated with TCP flows is an essential step for network security and traffic engineering. The classic way to identify flows, i.e. looking at...
Laurent Bernaille, Renata Teixeira, Ismael Akodken...
KDD
2003
ACM
150views Data Mining» more  KDD 2003»
14 years 10 months ago
Learning relational probability trees
Classification trees are widely used in the machine learning and data mining communities for modeling propositional data. Recent work has extended this basic paradigm to probabili...
Jennifer Neville, David Jensen, Lisa Friedland, Mi...