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» Compiling Bayesian Networks Using Variable Elimination
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JETAI
1998
110views more  JETAI 1998»
13 years 7 months ago
Independency relationships and learning algorithms for singly connected networks
Graphical structures such as Bayesian networks or Markov networks are very useful tools for representing irrelevance or independency relationships, and they may be used to e cientl...
Luis M. de Campos
KR
2004
Springer
14 years 25 days ago
GAI Networks for Utility Elicitation
This paper deals with preference representation and elicitation in the context of multiattribute utility theory under risk. Assuming the decision maker behaves according to the EU...
Christophe Gonzales, Patrice Perny
PERVASIVE
2009
Springer
14 years 2 months ago
Methodologies for Continuous Cellular Tower Data Analysis
This paper presents novel methodologies for the analysis of continuous cellular tower data from 215 randomly sampled subjects in a major urban city. We demonstrate the potential of...
Nathan Eagle, John A. Quinn, Aaron Clauset
PERCOM
2009
ACM
14 years 2 months ago
Adaptive Linear Filtering Compression on Realtime Sensor Networks
Abstract—We present a lightweight lossless compression algorithm for realtime sensor networks. Our proposed Adaptive Linear Filtering Compression (ALFC) algorithm performs predic...
Aaron B. Kiely, Mingsen Xu, Wen-Zhan Song, Renjie ...
ECOOP
2000
Springer
13 years 11 months ago
Optimizing Java Programs in the Presence of Exceptions
The support for precise exceptions in Java, combined with frequent checks for runtime exceptions, leads to severe limitations on the compiler’s ability to perform program optimiz...
Manish Gupta, Jong-Deok Choi, Michael Hind