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JMLR
2010
132views more  JMLR 2010»
14 years 9 months ago
Learning Gradients: Predictive Models that Infer Geometry and Statistical Dependence
The problems of dimension reduction and inference of statistical dependence are addressed by the modeling framework of learning gradients. The models we propose hold for Euclidean...
Qiang Wu, Justin Guinney, Mauro Maggioni, Sayan Mu...
APN
2000
Springer
15 years 7 months ago
Pre- and Post-agglomerations for LTL Model Checking
One of the most efficient analysis technique is to reduce an original model into a simpler one such that the reduced model has the same properties than the original one. G. Berthel...
Denis Poitrenaud, Jean-François Pradat-Peyr...
ICCAD
2010
IEEE
140views Hardware» more  ICCAD 2010»
15 years 27 days ago
Polynomial datapath optimization using constraint solving and formal modelling
For a variety of signal processing applications polynomials are implemented in circuits. Recent work on polynomial datapath optimization achieved significant reductions of hardware...
Finn Haedicke, Bijan Alizadeh, Görschwin Fey,...
KRDB
2003
117views Database» more  KRDB 2003»
15 years 4 months ago
On a Unifying Framework for Comparing Knowledge Representation Schemes
Given the numerous knowledge representation models (KR-schemes) that have been proposed, it would be desirable to have a formal, unifying model for the description of a KR-scheme,...
Giorgos Flouris, Dimitris Plexousakis, Grigoris An...
RECOMB
2012
Springer
13 years 5 months ago
A Model for Biased Fractionation after Whole Genome Duplication
Background: Paralog reduction, the loss of duplicate genes after whole genome duplication (WGD) is a pervasive process. Whether this loss proceeds gene by gene or through deletion...
David Sankoff, Chunfang Zheng, Baoyong Wang