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CVPR
2010
IEEE
14 years 7 months ago
Efficient computation of robust low-rank matrix approximations in the presence of missing data using the L1 norm
The calculation of a low-rank approximation of a matrix is a fundamental operation in many computer vision applications. The workhorse of this class of problems has long been the ...
Anders Eriksson, Anton van den Hengel
ICALP
1998
Springer
15 years 1 months ago
Efficient Approximation Algorithms for the Subset-Sums Equality Problem
We investigate the problem of finding two nonempty disjoint subsets of a set of n positive integers, with the objective that the sums of the numbers in the two subsets be as close ...
Cristina Bazgan, Miklos Santha, Zsolt Tuza
ICML
2009
IEEE
15 years 10 months ago
Robot trajectory optimization using approximate inference
The general stochastic optimal control (SOC) problem in robotics scenarios is often too complex to be solved exactly and in near real time. A classical approximate solution is to ...
Marc Toussaint
SIGMOD
2001
ACM
229views Database» more  SIGMOD 2001»
15 years 9 months ago
A Robust, Optimization-Based Approach for Approximate Answering of Aggregate Queries
The ability to approximately answer aggregation queries accurately and efficiently is of great benefit for decision support and data mining tools. In contrast to previous sampling...
Surajit Chaudhuri, Gautam Das, Vivek R. Narasayya
MOC
2000
76views more  MOC 2000»
14 years 9 months ago
Optimal approximation of stochastic differential equations by adaptive step-size control
We study the pathwise (strong) approximation of scalar stochastic differential equations with respect to the global error in the L2-norm. For equations with additive noise we estab...
Norbert Hofmann, Thomas Müller-Gronbach, Klau...