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» A linear approximation method for the Shapley value
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JMLR
2006
150views more  JMLR 2006»
14 years 9 months ago
Exact 1-Norm Support Vector Machines Via Unconstrained Convex Differentiable Minimization
Support vector machines utilizing the 1-norm, typically set up as linear programs (Mangasarian, 2000; Bradley and Mangasarian, 1998), are formulated here as a completely unconstra...
Olvi L. Mangasarian
MCS
2010
Springer
14 years 8 months ago
Goal-oriented a posteriori error estimates for transport problems
Some aspects of goal-oriented a posteriori error estimation are addressed in the context of steady convection-diffusion equations. The difference between the exact and approxima...
Dmitri Kuzmin, Sergey Korotov
APPROX
2005
Springer
111views Algorithms» more  APPROX 2005»
15 years 3 months ago
Sampling Bounds for Stochastic Optimization
A large class of stochastic optimization problems can be modeled as minimizing an objective function f that depends on a choice of a vector x ∈ X, as well as on a random external...
Moses Charikar, Chandra Chekuri, Martin Pál
VLSID
2002
IEEE
91views VLSI» more  VLSID 2002»
15 years 10 months ago
Rational ABCD Modeling of High-Speed Interconnects
This paper introduces a new numerical approximation technique, called the Differential Quadrature Method (DQM), in order to derive the rational ABCD matrix representing the high-s...
Qinwei Xu, Pinaki Mazumder
ATAL
2008
Springer
14 years 11 months ago
Sigma point policy iteration
In reinforcement learning, least-squares temporal difference methods (e.g., LSTD and LSPI) are effective, data-efficient techniques for policy evaluation and control with linear v...
Michael H. Bowling, Alborz Geramifard, David Winga...