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191
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APPROX
2008
Springer
15 years 8 months ago
2008
Springer
In the field of robust optimization, the goal is to provide solutions to combinatorial problems that hedge against variations of the numerical parameters. This constitutes an effor...
168
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ICML
2004
IEEE
16 years 7 months ago
2004
IEEE
Synchronous reinforcement learning (RL) algorithms with linear function approximation are representable as inhomogeneous matrix iterations of a special form (Schoknecht & Merk...
158
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AAMAS
2007
Springer
16 years 22 days ago
2007
Springer
Abstract. Reinforcement learning (RL) is a widely used learning paradigm for adaptive agents. There exist several convergent and consistent RL algorithms which have been intensivel...
168
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SDM
2010
SIAM
15 years 8 months ago
2010
SIAM
In recent years, matrix approximation for missing value prediction has emerged as an important problem in a variety of domains such as recommendation systems, e-commerce and onlin...
169
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SODA
2008
ACM
15 years 8 months ago
2008
ACM
In this paper, we present two techniques to analyze greedy approximation with nonsubmodular functions restricted submodularity and shifted submodularity. As an application of the ...