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» A spectral bundle method with bounds
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121
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JMLR
2010
143views more  JMLR 2010»
14 years 11 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, ...
CVPR
2009
IEEE
16 years 7 months ago
Projective Least-Squares: Global Solutions with Local Optimization
Recent work in multiple view geometry has focused on obtaining globally optimal solutions at the price of computational time efciency. On the other hand, traditional bundle adj...
Carl Olsson, Fredrik Kahl, Richard I. Hartley
113
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AMC
2011
14 years 7 months ago
Variational theory and domain decomposition for nonlocal problems
In this article we present the first results on domain decomposition methods for nonlocal operators. We present a nonlocal variational formulation for these operators and establi...
Burak Aksoylu, Michael L. Parks
95
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MOC
2000
96views more  MOC 2000»
15 years 11 days ago
Galerkin eigenvector approximations
How close are Galerkin eigenvectors to the best approximation available out of the trial subspace? Under a variety of conditions the Galerkin method gives an approximate eigenvecto...
Christopher Beattie
97
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SIAMJO
2008
86views more  SIAMJO 2008»
15 years 15 days ago
On the Second-Order Feasibility Cone: Primal-Dual Representation and Efficient Projection
We study the second-order feasibility cone F = {y IRn : My gT y} for given data (M, g). We construct a new representation for this cone and its dual based on the spectral decompo...
Alexandre Belloni, Robert M. Freund