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» Debugging Program Loops Using Approximate Modeling
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ATAL
2007
Springer
15 years 4 months ago
Model-based function approximation in reinforcement learning
Reinforcement learning promises a generic method for adapting agents to arbitrary tasks in arbitrary stochastic environments, but applying it to new real-world problems remains di...
Nicholas K. Jong, Peter Stone
JMLR
2006
145views more  JMLR 2006»
14 years 10 months ago
Ensemble Pruning Via Semi-definite Programming
An ensemble is a group of learning models that jointly solve a problem. However, the ensembles generated by existing techniques are sometimes unnecessarily large, which can lead t...
Yi Zhang 0006, Samuel Burer, W. Nick Street
EAAI
2007
101views more  EAAI 2007»
14 years 10 months ago
Fault detection for nonlinear systems with uncertain parameters based on the interval fuzzy model
In the paper an application of the interval fuzzy model (INFUMO) in fault detection for nonlinear systems with uncertain intervaltype parameters is presented. A confidence band f...
Simon Oblak, Igor Skrjanc, Saso Blazic
IHI
2012
217views Healthcare» more  IHI 2012»
13 years 5 months ago
Declarative privacy policy: finite models and attribute-based encryption
Regulations and policies regarding Electronic Health Information (EHI) are increasingly complex. Federal and State policy makers have called for both education to increase stakeho...
Peifung E. Lam, John C. Mitchell, Andre Scedrov, S...
ICCAD
2001
IEEE
102views Hardware» more  ICCAD 2001»
15 years 6 months ago
Simulation-Based Automatic Generation of Signomial and Posynomial Performance Models for Analog Integrated Circuit Sizing
This paper presents a method to automatically generate posynomial response surface models for the performance parameters of analog integrated circuits. The posynomial models enabl...
Walter Daems, Georges G. E. Gielen, Willy M. C. Sa...