495 search results - page 50 / 99 » Approximation algorithms for budgeted learning problems |
ECML
2005
Springer
15 years 5 months ago
2005
Springer
Abstract. Learning to act in an unknown partially observable domain is a difficult variant of the reinforcement learning paradigm. Research in the area has focused on model-free m...
102
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ESANN
2008
15 years 1 months ago
2008
Using multilayer perceptrons (MLPs) to approximate the state-action value function in reinforcement learning (RL) algorithms could become a nightmare due to the constant possibilit...
87
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FOCS
2008
IEEE
15 years 6 months ago
2008
IEEE
We study the problem of finding the minimum size DNF formula for a function f : {0, 1}d → {0, 1} given its truth table. We show that unless NP ⊆ DTIME(npoly(log n) ), there i...
JAIR
2010
14 years 10 months ago
2010
Domain-specific features are important in representing problem structure throughout machine learning and decision-theoretic planning. In planning, once state features are provide...
133
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TSMC
2010
14 years 6 months ago
2010
We study the problem of projecting high-dimensional tensor data on an unspecified Riemannian manifold onto some lower dimensional subspace1 without much distorting the pairwise geo...