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» Hierarchical exploration of large multivariate data sets
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BIODATAMINING
2008
96views more  BIODATAMINING 2008»
14 years 10 months ago
Fast approximate hierarchical clustering using similarity heuristics
Background: Agglomerative hierarchical clustering (AHC) is a common unsupervised data analysis technique used in several biological applications. Standard AHC methods require that...
Meelis Kull, Jaak Vilo
CVPR
2010
IEEE
15 years 5 months ago
Detecting and Parsing Architecture at City Scale from Range Data
We present a method for detecting and parsing buildings from unorganized 3D point clouds into a compact, hierarchical representation that is useful for high-level tasks. The input...
Alexander Toshev, Philippos Mordohai, Ben Taskar
BMCBI
2007
215views more  BMCBI 2007»
14 years 9 months ago
Learning causal networks from systems biology time course data: an effective model selection procedure for the vector autoregres
Background: Causal networks based on the vector autoregressive (VAR) process are a promising statistical tool for modeling regulatory interactions in a cell. However, learning the...
Rainer Opgen-Rhein, Korbinian Strimmer
ATAL
2003
Springer
15 years 3 months ago
Resource-aware exploration of the emergent dynamics of simulated systems
The emerging science of simulation enables us to explore the dynamics of large and complex systems even if a formal representation and analysis of the system is intractable and a ...
Sven Brueckner, H. Van Dyke Parunak
PAMI
2011
14 years 4 months ago
Action Recognition Using Mined Hierarchical Compound Features
—The field of Action Recognition has seen a large increase in activity in recent years. Much of the progress has been through incorporating ideas from single frame object recogn...
Andrew Gilbert, John Illingworth, Richard Bowden