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ICCV
2003
IEEE
14 years 9 months ago
Globally Convergent Autocalibration
Existing autocalibration techniques use numerical optimization algorithms that are prone to the problem of local minima. To address this problem, we have developed a method where ...
Arrigo Benedetti, Alessandro Busti, Michela Farenz...
EMO
2005
Springer
123views Optimization» more  EMO 2005»
14 years 28 days ago
Initial Population Construction for Convergence Improvement of MOEAs
Nearly all Multi-Objective Evolutionary Algorithms (MOEA) rely on random generation of initial population. In large and complex search spaces, this random method often leads to an ...
Christian Haubelt, Jürgen Gamenik, Jürge...
ORL
2008
115views more  ORL 2008»
13 years 6 months ago
On the convergence of stochastic dual dynamic programming and related methods
We discuss the almost-sure convergence of a broad class of sampling algorithms for multi-stage stochastic linear programs. We provide a convergence proof based on the finiteness o...
Andrew B. Philpott, Z. Guan
CDC
2008
IEEE
123views Control Systems» more  CDC 2008»
14 years 1 months ago
On distributed averaging algorithms and quantization effects
—We consider distributed iterative algorithms for the averaging problem over time-varying topologies. Our focus is on the convergence time of such algorithms when complete (unqua...
Angelia Nedic, Alexander Olshevsky, Asuman E. Ozda...
INFOCOM
2008
IEEE
14 years 1 months ago
Which Distributed Averaging Algorithm Should I Choose for my Sensor Network?
Average consensus and gossip algorithms have recently received significant attention, mainly because they constitute simple and robust algorithms for distributed information proc...
Patrick Denantes, Florence Bénézit, ...