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PKDD
1999
Springer
90views Data Mining» more  PKDD 1999»
15 years 4 months ago
Learning from Highly Structured Data by Decomposition
This paper addresses the problem of learning from highly structured data. Speci cally, it describes a procedure, called decomposition, that allows a learner to access automatically...
René MacKinney-Romero, Christophe G. Giraud...
PLDI
2012
ACM
13 years 2 months ago
Speculative separation for privatization and reductions
Automatic parallelization is a promising strategy to improve application performance in the multicore era. However, common programming practices such as the reuse of data structur...
Nick P. Johnson, Hanjun Kim, Prakash Prabhu, Ayal ...
TLDI
2005
ACM
135views Formal Methods» more  TLDI 2005»
15 years 5 months ago
Types for describing coordinated data structures
Coordinated data structures are sets of (perhaps unbounded) data structures where the nodes of each structure may share types with the corresponding nodes of the other structures....
Michael F. Ringenburg, Dan Grossman
GFKL
2004
Springer
137views Data Mining» more  GFKL 2004»
15 years 5 months ago
Density Estimation and Visualization for Data Containing Clusters of Unknown Structure
Abstract. A method for measuring the density of data sets that contain an unknown number of clusters of unknown sizes is proposed. This method, called Pareto Density Estimation (PD...
Alfred Ultsch
BMCBI
2008
103views more  BMCBI 2008»
15 years 1 days ago
Discovering multi-level structures in bio-molecular data through the Bernstein inequality
Background: The unsupervised discovery of structures (i.e. clusterings) underlying data is a central issue in several branches of bioinformatics. Methods based on the concept of s...
Alberto Bertoni, Giorgio Valentini