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» Approximation algorithms for the 0-extension problem
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ATAL
2007
Springer
16 years 26 days 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
PROCEDIA
2010
75views more  PROCEDIA 2010»
15 years 5 months ago
Two derivative-free optimization algorithms for mesh quality improvement
High-quality meshes are essential in the solution of partial differential equations (PDEs), which arise in numerous science and engineering applications, as the mesh quality aff...
Jeonghyung Park, Suzanne M. Shontz
IPCO
1998
99views Optimization» more  IPCO 1998»
15 years 8 months ago
Non-approximability Results for Scheduling Problems with Minsum Criteria
We provide several non-approximability results for deterministic scheduling problems whose objective is to minimize the total job completion time. Unless P = NP, none of the probl...
Han Hoogeveen, Petra Schuurman, Gerhard J. Woeging...
ANOR
2007
165views more  ANOR 2007»
15 years 6 months ago
Financial scenario generation for stochastic multi-stage decision processes as facility location problems
The quality of multi-stage stochastic optimization models as they appear in asset liability management, energy planning, transportation, supply chain management, and other applicat...
Ronald Hochreiter, Georg Ch. Pflug
ANOR
2010
112views more  ANOR 2010»
15 years 5 months ago
Online stochastic optimization under time constraints
This paper considers online stochastic optimization problems where uncertainties are characterized by a distribution that can be sampled and where time constraints severely limit t...
Pascal Van Hentenryck, Russell Bent, Eli Upfal