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» Gradient Convergence in Gradient methods with Errors
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ICASSP
2010
IEEE
14 years 12 months ago
Iterated smoothing for accelerated gradient convex minimization in signal processing
In this paper, we consider the problem of minimizing a non-smooth convex problem using first-order methods. The number of iterations required to guarantee a certain accuracy for ...
Tobias Lindstrøm Jensen, Jan Østerga...
SPAA
1990
ACM
15 years 3 months ago
A New Preconditioner for the Parallel Solution of Positive Definite Toeplitz Systems
We introduce a new preconditioner for solving a symmetric Toeplitz system of equations by the conjugate gradient method. This choice leads to an algorithm which is particularly sui...
Dario Bini, Fabio Di Benedetto
NIPS
2007
15 years 1 months ago
Incremental Natural Actor-Critic Algorithms
We present four new reinforcement learning algorithms based on actor-critic and natural-gradient ideas, and provide their convergence proofs. Actor-critic reinforcement learning m...
Shalabh Bhatnagar, Richard S. Sutton, Mohammad Gha...
ICML
2003
IEEE
16 years 16 days ago
Optimization with EM and Expectation-Conjugate-Gradient
We show a close relationship between the Expectation - Maximization (EM) algorithm and direct optimization algorithms such as gradientbased methods for parameter learning. We iden...
Ruslan Salakhutdinov, Sam T. Roweis, Zoubin Ghahra...
ICPR
2008
IEEE
16 years 28 days ago
Accelerating active contour algorithms with the Gradient Diffusion Field
Active contours were proposed by Kass et al. as a way to represent the contours of an image. Although the method is simple, one of its shortcomings is its inability to converge in...
Willie Kiser, Pradeep Sen, Chris Musial