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» Machine Learning by Function Decomposition
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124
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ICML
1996
IEEE
15 years 5 months ago
A Convergent Reinforcement Learning Algorithm in the Continuous Case: The Finite-Element Reinforcement Learning
This paper presents a direct reinforcement learning algorithm, called Finite-Element Reinforcement Learning, in the continuous case, i.e. continuous state-space and time. The eval...
Rémi Munos
91
Voted
NCA
2007
IEEE
15 years 1 months ago
A data reduction approach for resolving the imbalanced data issue in functional genomics
Learning from imbalanced data occurs frequently in many machine learning applications. One positive example to thousands of negative instances is common in scientific applications...
Kihoon Yoon, Stephen Kwek
ICML
2003
IEEE
16 years 2 months ago
On Kernel Methods for Relational Learning
Kernel methods have gained a great deal of popularity in the machine learning community as a method to learn indirectly in highdimensional feature spaces. Those interested in rela...
Chad M. Cumby, Dan Roth
IJCAI
2007
15 years 3 months ago
Kernel Conjugate Gradient for Fast Kernel Machines
We propose a novel variant of the conjugate gradient algorithm, Kernel Conjugate Gradient (KCG), designed to speed up learning for kernel machines with differentiable loss functio...
Nathan D. Ratliff, J. Andrew Bagnell
ALT
2003
Springer
15 years 10 months ago
Intrinsic Complexity of Uniform Learning
Inductive inference is concerned with algorithmic learning of recursive functions. In the model of learning in the limit a learner successful for a class of recursive functions mus...
Sandra Zilles