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» Approximating Component Selection
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ADC
2006
Springer
120views Database» more  ADC 2006»
15 years 4 months ago
Approximate data mining in very large relational data
In this paper we discuss eNERF, an extended version of non-Euclidean relational fuzzy c-means (NERFCM) for approximate clustering in very large (unloadable) relational data. The e...
James C. Bezdek, Richard J. Hathaway, Christopher ...
ATAL
2004
Springer
15 years 3 months ago
Approximate Solutions for Partially Observable Stochastic Games with Common Payoffs
Partially observable decentralized decision making in robot teams is fundamentally different from decision making in fully observable problems. Team members cannot simply apply si...
Rosemary Emery-Montemerlo, Geoffrey J. Gordon, Jef...
STACS
2001
Springer
15 years 2 months ago
Approximation Algorithms for the Bottleneck Stretch Factor Problem
The stretch factor of a Euclidean graph is the maximum ratio of the distance in the graph between any two points and their Euclidean distance. Given a set S of n points in Rd, we ...
Giri Narasimhan, Michiel H. M. Smid
NIPS
2003
14 years 11 months ago
Approximate Policy Iteration with a Policy Language Bias
We study an approach to policy selection for large relational Markov Decision Processes (MDPs). We consider a variant of approximate policy iteration (API) that replaces the usual...
Alan Fern, Sung Wook Yoon, Robert Givan
TIP
2008
113views more  TIP 2008»
14 years 10 months ago
Phase Local Approximation (PhaseLa) Technique for Phase Unwrap From Noisy Data
The local polynomial approximation (LPA) is a nonparametric regression technique with pointwise estimation in a sliding window. We apply the LPA of the argument of cos and sin in o...
Vladimir Katkovnik, Jaakko Astola, Karen O. Egiaza...