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IJCAI
2003
13 years 9 months ago
A Learning Algorithm for Localizing People Based on Wireless Signal Strength that Uses Labeled and Unlabeled Data
This paper summarizes a probabilistic approach for localizing people through the signal strengths of a wireless IEEE 802.11b network. Our approach uses data labeled by ground trut...
Sebastian Thrun, Geoffrey J. Gordon, Frank Pfennin...
JMLR
2010
137views more  JMLR 2010»
13 years 2 months ago
Importance Sampling for Continuous Time Bayesian Networks
A continuous time Bayesian network (CTBN) uses a structured representation to describe a dynamic system with a finite number of states which evolves in continuous time. Exact infe...
Yu Fan, Jing Xu, Christian R. Shelton
ICANNGA
2009
Springer
145views Algorithms» more  ICANNGA 2009»
14 years 2 months ago
Supporting Scalable Bayesian Networks Using Configurable Discretizer Actuators
We propose a generalized model with configurable discretizer actuators as a solution to the problem of the discretization of massive numerical datasets. Our solution is based on a ...
Isaac Olusegun Osunmakinde, Antoine B. Bagula
BMCBI
2007
114views more  BMCBI 2007»
13 years 7 months ago
Large scale statistical inference of signaling pathways from RNAi and microarray data
Background: The advent of RNA interference techniques enables the selective silencing of biologically interesting genes in an efficient way. In combination with DNA microarray tec...
Holger Fröhlich, Mark Fellmann, Holger Sü...
ICIP
1998
IEEE
14 years 9 months ago
A Neural Network Approach for Reconstructing Surface Shape from Shading
In this work, a framework for the reconstruction of smooth surface shapes from shading images is presented. The method is based on using a backpropagationbased neural network for ...
Jezekiel Ben-Arie, Dibyendu Nandy