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» On the Convergence of Boosting Procedures
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JMIV
2006
124views more  JMIV 2006»
13 years 8 months ago
Iterative Total Variation Regularization with Non-Quadratic Fidelity
Abstract. A generalized iterative regularization procedure based on the total variation penalization is introduced for image denoising models with non-quadratic convex fidelity ter...
Lin He, Martin Burger, Stanley Osher
ANTSW
2008
Springer
13 years 10 months ago
Adaptive Particle Swarm Optimization
An adaptive particle swarm optimization (APSO) that features better search efficiency than classical particle swarm optimization (PSO) is presented. More importantly, it can perfor...
Zhi-hui Zhan, Jun Zhang
ICML
2007
IEEE
14 years 9 months ago
On one method of non-diagonal regularization in sparse Bayesian learning
In the paper we propose a new type of regularization procedure for training sparse Bayesian methods for classification. Transforming Hessian matrix of log-likelihood function to d...
Dmitry Kropotov, Dmitry Vetrov
CEC
2009
IEEE
14 years 3 months ago
Local search based evolutionary multi-objective optimization algorithm for constrained and unconstrained problems
Abstract— Evolutionary multi-objective optimization algorithms are commonly used to obtain a set of non-dominated solutions for over a decade. Recently, a lot of emphasis have be...
Karthik Sindhya, Ankur Sinha, Kalyanmoy Deb, Kaisa...
CDC
2008
IEEE
150views Control Systems» more  CDC 2008»
14 years 3 months ago
Subgradient methods and consensus algorithms for solving convex optimization problems
— In this paper we propose a subgradient method for solving coupled optimization problems in a distributed way given restrictions on the communication topology. The iterative pro...
Björn Johansson, Tamás Keviczky, Mikae...