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» A linear approximation method for the Shapley value
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JMLR
2006
150views more  JMLR 2006»
15 years 5 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
15 years 4 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 11 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»
16 years 6 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
15 years 7 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...