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2007
136views Robotics» more  RSS 2007»
15 years 1 months ago
The Stochastic Motion Roadmap: A Sampling Framework for Planning with Markov Motion Uncertainty
— We present a new motion planning framework that explicitly considers uncertainty in robot motion to maximize the probability of avoiding collisions and successfully reaching a ...
Ron Alterovitz, Thierry Siméon, Kenneth Y. ...
CSDA
2006
155views more  CSDA 2006»
14 years 11 months ago
Modelling the mean of a doubly stochastic Poisson process by functional data analysis
A new procedure for estimating the mean process of a doubly stochastic Poisson process is introduced. The proposed estimation is based on monotone piecewise cubic interpolation of...
P. R. Bouzas, Mariano J. Valderrama, Ana M. Aguile...
BMCBI
2010
181views more  BMCBI 2010»
14 years 12 months ago
Intensity dependent estimation of noise in microarrays improves detection of differentially expressed genes
Background: In many microarray experiments, analysis is severely hindered by a major difficulty: the small number of samples for which expression data has been measured. When one ...
Amit Zeisel, Amnon Amir, Wolfgang J. Köstler,...
ICML
2006
IEEE
16 years 18 days ago
Locally adaptive classification piloted by uncertainty
Locally adaptive classifiers are usually superior to the use of a single global classifier. However, there are two major problems in designing locally adaptive classifiers. First,...
Juan Dai, Shuicheng Yan, Xiaoou Tang, James T. Kwo...
WSCG
2000
132views more  WSCG 2000»
15 years 1 months ago
Adaptive Filtering for Progressive Monte Carlo Image Rendering
Image filtering is often applied as a post-process to Monte Carlo generated pictures, in order to reduce noise. In this paper we present an algorithm based on density estimation t...
Frank Suykens, Yves D. Willems