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» Approximate algorithms for neural-Bayesian approaches
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ICRA
2002
IEEE
106views Robotics» more  ICRA 2002»
15 years 9 months ago
An Improved Random Neighborhood Graph Approach
As a general framework to determine a collision-free feedback motion strategies, the Random Neighborhood Graph (RNG) approach [19] defines a global navigation function over an ap...
Libo Yang, Steven M. LaValle
PG
1999
IEEE
15 years 8 months ago
Mesh Approximation Using a Volume-Based Metric
In this paper we introduce a mesh approximation method that uses a volume-based metric. After a geometric simplification, we minimize the volume between the simplified mesh and th...
Pierre Alliez, Nathalie Laurent, Henri Sanson, Fra...
STOC
1995
ACM
145views Algorithms» more  STOC 1995»
15 years 7 months ago
Polynomial time approximation schemes for dense instances of NP-hard problems
We present a unified framework for designing polynomial time approximation schemes (PTASs) for “dense” instances of many NP-hard optimization problems, including maximum cut,...
Sanjeev Arora, David R. Karger, Marek Karpinski
CISS
2008
IEEE
15 years 10 months ago
Distributed processing in frames for sparse approximation
—Beyond signal processing applications, frames are also powerful tools for modeling the sensing and information processing of many biological and man-made systems that exhibit in...
Christopher J. Rozell
SWAT
2004
Springer
98views Algorithms» more  SWAT 2004»
15 years 9 months ago
Tight Approximability Results for Test Set Problems in Bioinformatics
In this paper, we investigate the test set problem and its variations that appear in a variety of applications. In general, we are given a universe of objects to be “distinguish...
Piotr Berman, Bhaskar DasGupta, Ming-Yang Kao