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» Directional Newton methods in n variables
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MOC
2002
77views more  MOC 2002»
13 years 4 months ago
Directional Newton methods in n variables
Directional Newton methods for functions f of n variables are shown to converge, under standard assumptions, to a solution of f(x) = 0. The rate of convergence is quadratic, for ne...
Yuri Levin, Adi Ben-Israel
CORR
2008
Springer
129views Education» more  CORR 2008»
13 years 4 months ago
Polynomial Linear Programming with Gaussian Belief Propagation
Abstract--Interior-point methods are state-of-the-art algorithms for solving linear programming (LP) problems with polynomial complexity. Specifically, the Karmarkar algorithm typi...
Danny Bickson, Yoav Tock, Ori Shental, Danny Dolev
BMCBI
2008
186views more  BMCBI 2008»
13 years 4 months ago
Variable selection for large p small n regression models with incomplete data: Mapping QTL with epistases
Background: Identifying quantitative trait loci (QTL) for both additive and epistatic effects raises the statistical issue of selecting variables from a large number of candidates...
Min Zhang, Dabao Zhang, Martin T. Wells
JMLR
2010
143views more  JMLR 2010»
13 years 3 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, ...
EOR
2008
93views more  EOR 2008»
13 years 4 months ago
Approximate methods for convex minimization problems with series-parallel structure
Consider a problem of minimizing a separable, strictly convex, monotone and differentiable function on a convex polyhedron generated by a system of m linear inequalities. The probl...
Adi Ben-Israel, Genrikh Levin, Yuri Levin, Boris R...