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NIPS
2008
13 years 6 months ago
On the Generalization Ability of Online Strongly Convex Programming Algorithms
This paper examines the generalization properties of online convex programming algorithms when the loss function is Lipschitz and strongly convex. Our main result is a sharp bound...
Sham M. Kakade, Ambuj Tewari
SIAMSC
2010
143views more  SIAMSC 2010»
13 years 3 months ago
Computing and Deflating Eigenvalues While Solving Multiple Right-Hand Side Linear Systems with an Application to Quantum Chromod
Abstract. We present a new algorithm that computes eigenvalues and eigenvectors of a Hermitian positive definite matrix while solving a linear system of equations with Conjugate G...
Andreas Stathopoulos, Konstantinos Orginos
FOCM
2010
161views more  FOCM 2010»
13 years 3 months ago
The Asymptotics of Wilkinson's Shift: Loss of Cubic Convergence
One of the most widely used methods for eigenvalue computation is the QR iteration with Wilkinson’s shift: here the shift s is the eigenvalue of the bottom 2 × 2 principal mino...
Ricardo S. Leite, Nicolau C. Saldanha, Carlos Tome...
EOR
2007
117views more  EOR 2007»
13 years 5 months ago
Simultaneous perturbation stochastic approximation of nonsmooth functions
A simultaneous perturbation stochastic approximation (SPSA) method has been developed in this paper, using the operators of perturbation with the Lipschitz density function. This ...
Vaida Bartkute, Leonidas Sakalauskas
CVIU
2008
132views more  CVIU 2008»
13 years 4 months ago
Global parametric image alignment via high-order approximation
The estimation of parametric global motion is one of the cornerstones of computer vision. Such schemes are able to estimate various motion models (translation, rotation, affine, p...
Yosi Keller, Amir Averbuch