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» Approximate convex decomposition
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ORL
2011
14 years 4 months ago
Convex approximations to sparse PCA via Lagrangian duality
We derive a convex relaxation for cardinality constrained Principal Component Analysis (PCA) by using a simple representation of the L1 unit ball and standard Lagrangian duality. ...
Ronny Luss, Marc Teboulle
ICPR
2008
IEEE
15 years 10 months ago
Robust decomposition of a digital curve into convex and concave parts
We propose a linear in time and easy-to-implement algorithm that robustly decomposes a digital curve into convex and concave parts. This algorithm is based on classical tools in d...
Tristan Roussillon, Isabelle Sivignon, Laure Tougn...
FOCM
2010
97views more  FOCM 2010»
14 years 8 months ago
Self-Concordant Barriers for Convex Approximations of Structured Convex Sets
We show how to approximate the feasible region of structured convex optimization problems by a family of convex sets with explicitly given and efficient (if the accuracy of the ap...
Levent Tunçel, Arkadi Nemirovski
MP
2006
60views more  MP 2006»
14 years 9 months ago
Simple integer recourse models: convexity and convex approximations
Willem K. Klein Haneveld, Leen Stougie, Maarten H....
CORR
2010
Springer
143views Education» more  CORR 2010»
14 years 7 months ago
CUR from a Sparse Optimization Viewpoint
The CUR decomposition provides an approximation of a matrix X that has low reconstruction error and that is sparse in the sense that the resulting approximation lies in the span o...
Jacob Bien, Ya Xu, Michael W. Mahoney