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» Approximate algorithms for neural-Bayesian approaches
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ICRA
2002
IEEE
106views Robotics» more  ICRA 2002»
15 years 2 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 2 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 1 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 4 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 3 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