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SIAMJO
2008
72views more  SIAMJO 2008»
15 years 15 days ago
A Sample Approximation Approach for Optimization with Probabilistic Constraints
We study approximations of optimization problems with probabilistic constraints in which the original distribution of the underlying random vector is replaced with an empirical dis...
James Luedtke, Shabbir Ahmed
94
Voted
TSP
2010
14 years 7 months ago
A continuous-time linear system identification method for slowly sampled data
Both direct and indirect methods exist for identifying continuous-time linear systems. A direct method estimates continuous-time input and output signals from their samples and the...
Damián Marelli, Minyue Fu
101
Voted
ICPR
2006
IEEE
16 years 1 months ago
Robust Tracking of Multiple People in Crowds Using Laser Range Scanners
Laser based people tracking systems have been developed for mobile robotic or intelligent surveillance areas. Existing systems rely on laser point clustering to extract object loc...
Jinshi Cui, Hongbin Zha, Huijing Zhao, Ryosuke Shi...
EDBT
2009
ACM
110views Database» more  EDBT 2009»
15 years 5 months ago
A sampling approach for XML query selectivity estimation
As the Extensible Markup Language (XML) rapidly establishes itself as the de facto standard for presenting, storing, and exchanging data on the Internet, large volume of XML data ...
Cheng Luo, Zhewei Jiang, Wen-Chi Hou, Feng Yu, Qia...
ICANN
2010
Springer
15 years 1 months ago
Empirical Analysis of the Divergence of Gibbs Sampling Based Learning Algorithms for Restricted Boltzmann Machines
Abstract. Learning algorithms relying on Gibbs sampling based stochastic approximations of the log-likelihood gradient have become a common way to train Restricted Boltzmann Machin...
Asja Fischer, Christian Igel