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MP
2007
89views more  MP 2007»
13 years 4 months ago
Globally convergent limited memory bundle method for large-scale nonsmooth optimization
Many practical optimization problems involve nonsmooth (that is, not necessarily differentiable) functions of thousands of variables. In the paper [Haarala, Miettinen, M¨akel¨a,...
Napsu Haarala, Kaisa Miettinen, Marko M. Mäke...
JOTA
2011
149views more  JOTA 2011»
12 years 11 months ago
Globally Convergent Cutting Plane Method for Nonconvex Nonsmooth Minimization
: Nowadays, solving nonsmooth (not necessarily differentiable) optimization problems plays a very important role in many areas of industrial applications. Most of the algorithms d...
Napsu Karmitsa, Mario Tanaka Filho, José He...
ICCV
2007
IEEE
14 years 6 months ago
Out-of-Core Bundle Adjustment for Large-Scale 3D Reconstruction
Large-scale 3D reconstruction has recently received much attention from the computer vision community. Bundle adjustment is a key component of 3D reconstruction problems. However,...
Kai Ni, Drew Steedly, Frank Dellaert
SIAMJO
2008
92views more  SIAMJO 2008»
13 years 4 months ago
A Trust Region Spectral Bundle Method for Nonconvex Eigenvalue Optimization
We present a nonsmooth optimization technique for nonconvex maximum eigenvalue functions and for nonsmooth functions which are infinite maxima of eigenvalue functions. We prove glo...
Pierre Apkarian, Dominikus Noll, O. Prot
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, ...