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APPROX
2005
Springer
136views Algorithms» more  APPROX 2005»
16 years 11 days ago
What About Wednesday? Approximation Algorithms for Multistage Stochastic Optimization
The field of stochastic optimization studies decision making under uncertainty, when only probabilistic information about the future is available. Finding approximate solutions to...
Anupam Gupta, Martin Pál, R. Ravi, Amitabh ...
BMCBI
2002
108views more  BMCBI 2002»
15 years 6 months ago
A memory-efficient dynamic programming algorithm for optimal alignment of a sequence to an RNA secondary structure
Background: Covariance models (CMs) are probabilistic models of RNA secondary structure, analogous to profile hidden Markov models of linear sequence. The dynamic programming algo...
Sean R. Eddy
MICCAI
2006
Springer
16 years 7 months ago
A Learning Based Algorithm for Automatic Extraction of the Cortical Sulci
This paper presents a learning based method for automatic extraction of the major cortical sulci from MRI volumes or extracted surfaces. Instead of using a few pre-defined rules su...
Songfeng Zheng, Zhuowen Tu, Alan L. Yuille, Allan ...
PODS
2008
ACM
159views Database» more  PODS 2008»
16 years 7 months ago
Approximation algorithms for clustering uncertain data
There is an increasing quantity of data with uncertainty arising from applications such as sensor network measurements, record linkage, and as output of mining algorithms. This un...
Graham Cormode, Andrew McGregor
ECCV
2002
Springer
16 years 8 months ago
A Stochastic Algorithm for 3D Scene Segmentation and Reconstruction
In this paper, we present a stochastic algorithm by effective Markov chain Monte Carlo (MCMC) for segmenting and reconstructing 3D scenes. The objective is to segment a range image...
Feng Han, Zhuowen Tu, Song Chun Zhu