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» Smooth Optimization with Approximate Gradient
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MP
2002
84views more  MP 2002»
13 years 7 months ago
A decomposition procedure based on approximate Newton directions
The efficient solution of large-scale linear and nonlinear optimization problems may require exploiting any special structure in them in an efficient manner. We describe and analy...
Antonio J. Conejo, Francisco J. Nogales, Francisco...
NIPS
2007
13 years 9 months ago
What makes some POMDP problems easy to approximate?
Point-based algorithms have been surprisingly successful in computing approximately optimal solutions for partially observable Markov decision processes (POMDPs) in high dimension...
David Hsu, Wee Sun Lee, Nan Rong
PG
2002
IEEE
14 years 18 days ago
Approximation with Active B-Spline Curves and Surfaces
An active contour model for parametric curve and surface approximation is presented. The active curve or surface adapts to the model shape to be approximated in an optimization al...
Helmut Pottmann, Stefan Leopoldseder, Michael Hofe...
SIAMMA
2010
63views more  SIAMMA 2010»
13 years 2 months ago
Sparse Tensor Product Wavelet Approximation of Singular Functions
Abstract. On product domains, sparse-grid approximation yields optimal, dimension-independent convergence rates when the function that is approximated has L2-bounded mixed derivati...
Monique Dauge, Rob Stevenson
ECML
2004
Springer
14 years 1 months ago
Associative Clustering
This report contains derivations which did not fit into the paper [3]. Associative clustering (AC) is a method for separately clustering two data sets when one-to-one association...
Janne Sinkkonen, Janne Nikkilä, Leo Lahti, Sa...