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FOCS
1999
IEEE
15 years 10 months ago
Learning Mixtures of Gaussians
Mixtures of Gaussians are among the most fundamental and widely used statistical models. Current techniques for learning such mixtures from data are local search heuristics with w...
Sanjoy Dasgupta
CEC
2007
IEEE
15 years 10 months ago
Support vector machines for computing action mappings in learning classifier systems
XCS with Computed Action, briefly XCSCA, is a recent extension of XCS to tackle problems involving a large number of discrete actions. In XCSCA the classifier action is computed wi...
Daniele Loiacono, Andrea Marelli, Pier Luca Lanzi
AAAI
2008
15 years 8 months ago
Potential-based Shaping in Model-based Reinforcement Learning
Potential-based shaping was designed as a way of introducing background knowledge into model-free reinforcement-learning algorithms. By identifying states that are likely to have ...
John Asmuth, Michael L. Littman, Robert Zinkov
IJDMMM
2008
87views more  IJDMMM 2008»
15 years 6 months ago
Is an ordinal class structure useful in classifier learning?
In recent years, a number of machine learning algorithms have been developed for the problem of ordinal classification. These algorithms try to exploit, in one way or the other, t...
Jens C. Huhn, Eyke Hüllermeier
KDD
2009
ACM
173views Data Mining» more  KDD 2009»
16 years 7 months ago
The offset tree for learning with partial labels
We present an algorithm, called the offset tree, for learning in situations where a loss associated with different decisions is not known, but was randomly probed. The algorithm i...
Alina Beygelzimer, John Langford