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AIIA
2003
Springer
14 years 1 months ago
Improving the SLA Algorithm Using Association Rules
A bayesian network is an appropriate tool for working with uncertainty and probability, that are typical of real-life applications. In literature we find different approaches for b...
Evelina Lamma, Fabrizio Riguzzi, Andrea Stambazzi,...
KDD
2009
ACM
249views Data Mining» more  KDD 2009»
14 years 9 months ago
Drosophila gene expression pattern annotation using sparse features and term-term interactions
The Drosophila gene expression pattern images document the spatial and temporal dynamics of gene expression and they are valuable tools for explicating the gene functions, interac...
Shuiwang Ji, Lei Yuan, Ying-Xin Li, Zhi-Hua Zhou, ...
ICDM
2010
IEEE
228views Data Mining» more  ICDM 2010»
13 years 6 months ago
Active Learning from Multiple Noisy Labelers with Varied Costs
In active learning, where a learning algorithm has to purchase the labels of its training examples, it is often assumed that there is only one labeler available to label examples, ...
Yaling Zheng, Stephen D. Scott, Kun Deng
BMCBI
2010
144views more  BMCBI 2010»
13 years 8 months ago
Graph-based clustering and characterization of repetitive sequences in next-generation sequencing data
Background: The investigation of plant genome structure and evolution requires comprehensive characterization of repetitive sequences that make up the majority of higher plant nuc...
Petr Novák, Pavel Neumann, Jirí Maca...
SOFTWARE
2002
13 years 8 months ago
Temporal Probabilistic Concepts from Heterogeneous Data Sequences
We consider the problem of characterisation of sequences of heterogeneous symbolic data that arise from a common underlying temporal pattern. The data, which are subject to impreci...
Sally I. McClean, Bryan W. Scotney, Fiona Palmer