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» A local approximation algorithm for maximum weight matching
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CORR
2012
Springer
170views Education» more  CORR 2012»
13 years 5 months ago
What Cannot be Learned with Bethe Approximations
We address the problem of learning the parameters in graphical models when inference is intractable. A common strategy in this case is to replace the partition function with its B...
Uri Heinemann, Amir Globerson
ICCAD
2004
IEEE
180views Hardware» more  ICCAD 2004»
15 years 6 months ago
Physical placement driven by sequential timing analysis
Traditional timing-driven placement considers only combinational delays and does not take into account the potential of subsequent sequential optimization steps. As a result, the ...
Aaron P. Hurst, Philip Chong, Andreas Kuehlmann
RECOMB
2001
Springer
15 years 10 months ago
A new approach to sequence comparison: normalized sequence alignment
The Smith-Waterman algorithm for local sequence alignment is one of the most important techniques in computational molecular biology. This ingenious dynamic programming approach w...
Abdullah N. Arslan, Ömer Egecioglu, Pavel A. ...
CAGD
2005
116views more  CAGD 2005»
14 years 9 months ago
A sharpness dependent filter for mesh smoothing
In this paper, we propose a sharpness dependent filter design based on the fairing of surface normal, whereby the filtering algorithm automatically selects a filter. This may be a...
Chun-Yen Chen, Kuo-Young Cheng
ICRA
2008
IEEE
150views Robotics» more  ICRA 2008»
15 years 4 months ago
A Bayesian approach to empirical local linearization for robotics
— Local linearizations are ubiquitous in the control of robotic systems. Analytical methods, if available, can be used to obtain the linearization, but in complex robotics system...
Jo-Anne Ting, Aaron D'Souza, Sethu Vijayakumar, St...