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NIPS
2001
13 years 9 months ago
Variance Reduction Techniques for Gradient Estimates in Reinforcement Learning
Policy gradient methods for reinforcement learning avoid some of the undesirable properties of the value function approaches, such as policy degradation (Baxter and Bartlett, 2001...
Evan Greensmith, Peter L. Bartlett, Jonathan Baxte...
BMCBI
2010
160views more  BMCBI 2010»
13 years 8 months ago
Quantitative model for inferring dynamic regulation of the tumour suppressor gene p53
Background: The availability of various "omics" datasets creates a prospect of performing the study of genomewide genetic regulatory networks. However, one of the major ...
Junbai Wang, Tianhai Tian
DOLAP
2006
ACM
14 years 1 months ago
Designing what-if analysis: towards a methodology
In order to be able to evaluate beforehand the impact of a strategical or tactical move, decision makers need reliable previsional systems. What-if analysis satisfies this need b...
Matteo Golfarelli, Stefano Rizzi, Andrea Proli
RBAC
2000
129views more  RBAC 2000»
13 years 9 months ago
Enabling technologies for role based online decision engines
: Enabling Technologies for Role Based Online Decision Engines Thomas Hildmann, Thomas Gebhardt 22-Feb-2000 The goal of our work at the Technical University of Berlin is to develop...
Thomas Gebhardt, Thomas Hildmann
SC
2009
ACM
14 years 2 months ago
Evaluating the impact of inaccurate information in utility-based scheduling
Proponents of utility-based scheduling policies have shown the potential for a 100–1400% increase in value-delivered to users when used in lieu of traditional approaches such as...
Alvin AuYoung, Amin Vahdat, Alex C. Snoeren