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JMLR
2010
143views more  JMLR 2010»
13 years 6 months ago
A Quasi-Newton Approach to Nonsmooth Convex Optimization Problems in Machine Learning
We extend the well-known BFGS quasi-Newton method and its memory-limited variant LBFGS to the optimization of nonsmooth convex objectives. This is done in a rigorous fashion by ge...
Jin Yu, S. V. N. Vishwanathan, Simon Günter, ...
CEC
2008
IEEE
14 years 2 months ago
Examination of multi-objective optimization method for global search using DIRECT and GA
— A number of multi-objective genetic algorithms (MOGAs) have been developed to obtain Pareto optimal solutions for multi-objective optimization problems. However, as these metho...
Luyi Wang, Hiroyuki Ishida, Tomoyuki Hiroyasu, Mit...
MEMETIC
2010
311views more  MEMETIC 2010»
13 years 2 months ago
Iterated local search with Powell's method: a memetic algorithm for continuous global optimization
In combinatorial solution spaces Iterated Local Search (ILS) turns out to be exceptionally successful. The question arises: is ILS also capable of improving the optimization proces...
Oliver Kramer
IOR
2007
57views more  IOR 2007»
13 years 7 months ago
A Model Reference Adaptive Search Method for Global Optimization
Jiaqiao Hu, Michael C. Fu, Steven I. Marcus
ECCV
2006
Springer
14 years 9 months ago
Globally Optimal Active Contours, Sequential Monte Carlo and On-Line Learning for Vessel Segmentation
In this paper we propose a Particle Filter-based propagation approach for the segmentation of vascular structures in 3D volumes. Because of pathologies and inhomogeneities, many de...
Charles Florin, Nikos Paragios, James Williams