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UAI
2008
13 years 8 months ago
Partitioned Linear Programming Approximations for MDPs
Approximate linear programming (ALP) is an efficient approach to solving large factored Markov decision processes (MDPs). The main idea of the method is to approximate the optimal...
Branislav Kveton, Milos Hauskrecht
CORR
2010
Springer
198views Education» more  CORR 2010»
13 years 4 months ago
Convex Graph Invariants
The structural properties of graphs are usually characterized in terms of invariants, which are functions of graphs that do not depend on the labeling of the nodes. In this paper ...
Venkat Chandrasekaran, Pablo A. Parrilo, Alan S. W...
NIPS
2001
13 years 8 months ago
Estimating Car Insurance Premia: a Case Study in High-Dimensional Data Inference
Estimating insurance premia from data is a difficult regression problem for several reasons: the large number of variables, many of which are discrete, and the very peculiar shape...
Nicolas Chapados, Yoshua Bengio, Pascal Vincent, J...
CEC
2008
IEEE
14 years 1 months ago
A study on constrained MA using GA and SQP: Analytical vs. finite-difference gradients
— Many deterministic algorithms in the context of constrained optimization require the first-order derivatives, or the gradient vectors, of the objective and constraint function...
Stephanus Daniel Handoko, Chee Keong Kwoh, Yew-Soo...
ICIP
1999
IEEE
14 years 9 months ago
The Sinc-Approximating Kernels of Classical Polynomial Interpolation
A classical approach to interpolation of sampled data is polynomial interpolation. However, from the sampling theorem it follows that the ideal approach to interpolation is to con...
Erik H. W. Meijering, Wiro J. Niessen, Max A. Vier...