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» Convex Programming Methods for Global Optimization
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JMLR
2012
11 years 7 months ago
Minimax-Optimal Rates For Sparse Additive Models Over Kernel Classes Via Convex Programming
Sparse additive models are families of d-variate functions with the additive decomposition f∗ = ∑j∈S f∗ j , where S is an unknown subset of cardinality s d. In this paper,...
Garvesh Raskutti, Martin J. Wainwright, Bin Yu
SIAMJO
2010
87views more  SIAMJO 2010»
13 years 3 months ago
A Second Derivative SQP Method: Global Convergence
Abstract. Sequential quadratic programming (SQP) methods form a class of highly efficient algorithms for solving nonlinearly constrained optimization problems. Although second deri...
Nicholas I. M. Gould, Daniel P. Robinson
ECCV
2010
Springer
13 years 8 months ago
Practical Methods For Convex Multi-View Reconstruction
Globally optimal formulations of geometric computer vision problems comprise an exciting topic in multiple view geometry. These approaches are unaffected by the quality of a provid...
MOC
2002
101views more  MOC 2002»
13 years 4 months ago
Global and uniform convergence of subspace correction methods for some convex optimization problems
This paper gives some global and uniform convergence estimates for a class of subspace correction (based on space decomposition) iterative methods applied to some unconstrained con...
Xue-Cheng Tai, Jinchao Xu
CASC
2010
Springer
151views Mathematics» more  CASC 2010»
13 years 4 months ago
Supporting Global Numerical Optimization of Rational Functions by Generic Symbolic Convexity Tests
Convexity is an important property in nonlinear optimization since it allows to apply efficient local methods for finding global solutions. We propose to apply symbolic methods t...
Winfried Neun, Thomas Sturm, Stefan Vigerske