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CPAIOR
2009
Springer
15 years 11 months ago
Learning How to Propagate Using Random Probing
Abstract. In constraint programming there are often many choices regarding the propagation method to be used on the constraints of a problem. However, simple constraint solvers usu...
Efstathios Stamatatos, Kostas Stergiou
SIGECOM
2009
ACM
114views ECommerce» more  SIGECOM 2009»
15 years 11 months ago
Policy teaching through reward function learning
Policy teaching considers a Markov Decision Process setting in which an interested party aims to influence an agent’s decisions by providing limited incentives. In this paper, ...
Haoqi Zhang, David C. Parkes, Yiling Chen
FOCS
2008
IEEE
15 years 11 months ago
Hardness of Minimizing and Learning DNF Expressions
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...
Subhash Khot, Rishi Saket
ICPP
2008
IEEE
15 years 11 months ago
Dynamic Meta-Learning for Failure Prediction in Large-Scale Systems: A Case Study
Despite great efforts on the design of ultra-reliable components, the increase of system size and complexity has outpaced the improvement of component reliability. As a result, fa...
Jiexing Gu, Ziming Zheng, Zhiling Lan, John White,...
AGILEDC
2007
IEEE
15 years 11 months ago
Agile Program Management: Lessons Learned from the VeriSign Managed Security Services Team
This report examines how the VeriSign Managed Security Services team (MSS) has successfully extended agile software development practices to deal with a complex, multi-product dev...
Peter Hodgkins, Luke Hohmann