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» Exploiting Data Missingness in Bayesian Network Modeling
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81
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DCC
2010
IEEE
14 years 11 months ago
Neural Markovian Predictive Compression: An Algorithm for Online Lossless Data Compression
This work proposes a novel practical and general-purpose lossless compression algorithm named Neural Markovian Predictive Compression (NMPC), based on a novel combination of Bayesi...
Erez Shermer, Mireille Avigal, Dana Shapira
110
Voted
PKDD
2010
Springer
168views Data Mining» more  PKDD 2010»
14 years 11 months ago
Bayesian Knowledge Corroboration with Logical Rules and User Feedback
Current knowledge bases suffer from either low coverage or low accuracy. The underlying hypothesis of this work is that user feedback can greatly improve the quality of automatica...
Gjergji Kasneci, Jurgen Van Gael, Ralf Herbrich, T...
ICDE
2006
IEEE
201views Database» more  ICDE 2006»
16 years 1 months ago
Approximate Data Collection in Sensor Networks using Probabilistic Models
Wireless sensor networks are proving to be useful in a variety of settings. A core challenge in these networks is to minimize energy consumption. Prior database research has propo...
David Chu, Amol Deshpande, Joseph M. Hellerstein, ...
112
Voted
JSAC
2010
194views more  JSAC 2010»
14 years 11 months ago
Burst communication by means of buffer allocation in body sensor networks: Exploiting signal processing to reduce the number of
Abstract—Monitoring human movements using wireless sensory devices promises to revolutionize the delivery of healthcare services. Such platforms use inertial information of their...
Hassan Ghasemzadeh, Vitali Loseu, Sarah Ostadabbas...
BIBE
2008
IEEE
111views Bioinformatics» more  BIBE 2008»
15 years 2 months ago
Structure learning for biomolecular pathways containing cycles
Bayesian network structure learning is a useful tool for elucidation of regulatory structures of biomolecular pathways. The approach however is limited by its acyclicity constraint...
S. Itani, Karen Sachs, Garry P. Nolan, M. A. Dahle...