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ML
2002
ACM
143views Machine Learning» more  ML 2002»
15 years 4 months ago
A Sparse Sampling Algorithm for Near-Optimal Planning in Large Markov Decision Processes
An issue that is critical for the application of Markov decision processes MDPs to realistic problems is how the complexity of planning scales with the size of the MDP. In stochas...
Michael J. Kearns, Yishay Mansour, Andrew Y. Ng
141
Voted
AAAI
1997
15 years 6 months ago
Summarizing CSP Hardness with Continuous Probability Distributions
We present empirical evidence that the distribution of e ort required to solve CSPs randomly generated at the 50% satis able point, when using a backtracking algorithm, can be app...
Daniel Frost, Irina Rish, Lluís Vila
SMI
2006
IEEE
135views Image Analysis» more  SMI 2006»
15 years 11 months ago
Laplace-Beltrami Eigenfunctions Towards an Algorithm That "Understands" Geometry
One of the challenges in geometry processing is to automatically reconstruct a higher-level representation from raw geometric data. For instance, computing a parameterization of a...
Bruno Lévy
122
Voted
PROCEDIA
2010
75views more  PROCEDIA 2010»
15 years 3 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
134
Voted
ANOR
2010
112views more  ANOR 2010»
15 years 3 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