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» Using Bayesian networks to analyze expression data
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ESOP
2011
Springer
14 years 9 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
15 years 7 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»
15 years 1 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 9 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»
16 years 6 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