Browsing by Keywords "Least squares"
Now showing items 1-8 of 8
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Büyük ölçekli doğrusal denklem sistemleri için hızlı ve gürbüz çözüm teknikleri
(IEEE, 2019-04)Büyük ölçekli doğrusal sistemlerin veri matrisi, sütunlar arası yüksek ilintiye ve genellikle yüksek durum numaralarına sahiptir. Bilinmeyenlerin, ölçümlerden En Küçük Kareler (EKK) tekniğiyle üretilmesi, ölçüm gürültüsünün, ... -
Cross-term free based bistatic radar system using sparse least squares
(SPIE, 2015)Passive Bistatic Radar (PBR) systems use illuminators of opportunity, such as FM, TV, and DAB broadcasts. The most common illuminator of opportunity used in PBR systems is the FM radio stations. Single FM channel based PBR ... -
Fast and robust solution techniques for large scale linear least squares problems
(Bilkent University, 2020-07)Momentum Iterative Hessian Sketch (M-IHS) techniques, a group of solvers for large scale linear Least Squares (LS) problems, are proposed and analyzed in detail. Proposed M-IHS techniques are obtained by incorporating the ... -
Goowe : geometrically optimum and online-weighted ensemble classifier for evolving data streams
(Bilkent University, 2016-08)Designing adaptive classifiers for an evolving data stream is a challenging task due to its size and dynamically changing nature. Combining individual classifiers in an online setting, the ensemble approach, is one of the ... -
GOOWE: geometrically optimum and online-weighted ensemble classifier for evolving data streams
(Association for Computing Machinery, 2018-01-25)Designing adaptive classifiers for an evolving data stream is a challenging task due to the data size and its dynamically changing nature. Combining individual classifiers in an online setting, the ensemble approach, is a ... -
On robust solutions to linear least squares problems affected by data uncertainty and implementation errors with application to stochastic signal modeling
(Elsevier, 2004)Engineering design problems, especially in signal and image processing, give rise to linear least squares problems arising from discretization of some inverse problem. The associated data are typically subject to error in ... -
Robust least squares methods under bounded data uncertainties
(Academic Press, 2015)We study the problem of estimating an unknown deterministic signal that is observed through an unknown deterministic data matrix under additive noise. In particular, we present a minimax optimization framework to the least ... -
Structured least squares problems and robust estimators
(IEEE, 2010-10-22)A novel approach is proposed to provide robust and accurate estimates for linear regression problems when both the measurement vector and the coefficient matrix are structured and subject to errors or uncertainty. A new ...
