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» Using Bayesian networks to analyze expression data
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ESOP
2011
Springer
14 years 1 months ago
Measure Transformer Semantics for Bayesian Machine Learning
Abstract. The Bayesian approach to machine learning amounts to inferring posterior distributions of random variables from a probabilistic model of how the variables are related (th...
Johannes Borgström, Andrew D. Gordon, Michael...
COLING
2000
14 years 11 months ago
Word Sense Disambiguation of Adjectives Using Probabilistic Networks
In this paper, word sense dismnbiguation (WSD) accuracy achievable by a probabilistic classifier, using very milfimal training sets, is investigated. \Ve made the assuml)tiou that...
Gerald Chao, Michael G. Dyer
TIT
2011
113views more  TIT 2011»
14 years 4 months ago
Asymptotic Capacity and Optimal Precoding in MIMO Multi-Hop Relay Networks
A multi-hop relaying system is analyzed where data sent by a multi-antenna source is relayed by successive multi-antenna relays until it reaches a multi-antenna destination. Assum...
Nadia Fawaz, Keyvan Zarifi, Mérouane Debbah...
RAID
2000
Springer
15 years 1 months ago
Transaction-Based Pseudonyms in Audit Data for Privacy Respecting Intrusion Detection
Abstract. Privacy and surveillance by intrusion detection are potentially conflicting organizational and legal requirements. In order to support a balanced solution, audit data is ...
Joachim Biskup, Ulrich Flegel
KDD
2003
ACM
148views Data Mining» more  KDD 2003»
15 years 10 months ago
A highly-usable projected clustering algorithm for gene expression profiles
Projected clustering has become a hot research topic due to its ability to cluster high-dimensional data. However, most existing projected clustering algorithms depend on some cri...
Kevin Y. Yip, David W. Cheung, Michael K. Ng