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TSP
2010
14 years 4 months ago
Methods for sparse signal recovery using Kalman filtering with embedded pseudo-measurement norms and quasi-norms
We present two simple methods for recovering sparse signals from a series of noisy observations. The theory of compressed sensing (CS) requires solving a convex constrained minimiz...
Avishy Carmi, Pini Gurfil, Dimitri Kanevsky
SOCO
2012
Springer
13 years 5 months ago
Variable mesh optimization for continuous optimization problems
Abstract Population-based meta-heuristics are algorithms that can obtain very good results for complex continuous optimization problems in a reduced amount of time. These search al...
Amilkar Puris, Rafael Bello, Daniel Molina, Franci...
ICPR
2008
IEEE
15 years 10 months ago
Solving quadratically constrained geometrical problems using lagrangian duality
In this paper we consider the problem of solving different pose and registration problems under rotational constraints. Traditionally, methods such as the iterative closest point ...
Carl Olsson, Anders Eriksson
ENDM
2010
100views more  ENDM 2010»
14 years 9 months ago
Large-scale multi-period precedence constrained knapsack problem: A mining application
We study an extension of the precedence constrained knapsack problem where the knapsack can be filled in multiple periods. This problem is known in the mining industry as the open...
Eduardo Moreno, Daniel G. Espinoza, Marcos Goycool...
CAI
2010
Springer
14 years 7 months ago
Constrained Longest Common Subsequence Computing Algorithms in Practice
The problem of finding a constrained longest common subsequence (CLCS) for the sequences A and B with respect to the sequence P was introduced recently. Its goal is to find a longe...
Sebastian Deorowicz, J. Obstoj