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» Topological grammars for data approximation
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BMCBI
2006
101views more  BMCBI 2006»
13 years 7 months ago
SynTReN: a generator of synthetic gene expression data for design and analysis of structure learning algorithms
Background: The development of algorithms to infer the structure of gene regulatory networks based on expression data is an important subject in bioinformatics research. Validatio...
Tim Van den Bulcke, Koen Van Leemput, Bart Naudts,...
IMC
2007
ACM
13 years 9 months ago
Learning network structure from passive measurements
The ability to discover network organization, whether in the form of explicit topology reconstruction or as embeddings that approximate topological distance, is a valuable tool. T...
Brian Eriksson, Paul Barford, Robert Nowak, Mark C...
COMPGEOM
2011
ACM
12 years 11 months ago
Reeb graphs: approximation and persistence
Given a continuous function f : X → IR on a topological space X, its level set f−1 (a) changes continuously as the real value a changes. Consequently, the connected components...
Tamal K. Dey, Yusu Wang
DMSN
2004
ACM
14 years 27 days ago
Optimization of in-network data reduction
We consider the in-network computation of approximate “big picture” summaries in bandwidth-constrained sensor networks. First we review early work on computing the Haar wavele...
Joseph M. Hellerstein, Wei Wang
DIALM
2004
ACM
113views Algorithms» more  DIALM 2004»
14 years 27 days ago
Gathering correlated data in sensor networks
In this paper, we consider energy-efficient gathering of correlated data in sensor networks. We focus on single-input coding strategies in order to aggregate correlated data. For ...
Pascal von Rickenbach, Roger Wattenhofer