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» Some new iterative methods with three-order convergence
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SAC
2011
ACM
13 years 2 months ago
A quasi-Newton acceleration for high-dimensional optimization algorithms
Abstract In many statistical problems, maximum likelihood estimation by an EM or MM algorithm suffers from excruciatingly slow convergence. This tendency limits the application of ...
Hua Zhou, David Alexander, Kenneth Lange
UAI
2003
13 years 9 months ago
On the Convergence of Bound Optimization Algorithms
Many practitioners who use EM and related algorithms complain that they are sometimes slow. When does this happen, and what can be done about it? In this paper, we study the gener...
Ruslan Salakhutdinov, Sam T. Roweis, Zoubin Ghahra...
ICPR
2010
IEEE
13 years 10 months ago
Fast Training of Object Detection Using Stochastic Gradient Descent
Training datasets for object detection problems are typically very large and Support Vector Machine (SVM) implementations are computationally complex. As opposed to these complex ...
Rob Wijnhoven, Peter H. N. De With
CCE
2004
13 years 7 months ago
Improving convergence of the stochastic decomposition algorithm by using an efficient sampling technique
This work focuses on the basic stochastic decomposition (SD) algorithm of Higle and Sen [J.L. Higle, S. Sen, Stochastic Decomposition, Kluwer Academic Publishers, 1996] for two-st...
José María Ponce-Ortega, Vicente Ric...
HPCA
2008
IEEE
14 years 8 months ago
Fabric convergence implications on systems architecture
Converged fabrics that support data, storage, and cluster networking in a unified fashion are desirable for their cost and manageability advantages. Recent trends towards higher-b...
Kevin Leigh, Parthasarathy Ranganathan, Jaspal Sub...