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ICONIP
2007
15 years 8 months ago
Principal Component Analysis for Sparse High-Dimensional Data
Abstract. Principal component analysis (PCA) is a widely used technique for data analysis and dimensionality reduction. Eigenvalue decomposition is the standard algorithm for solvi...
Tapani Raiko, Alexander Ilin, Juha Karhunen
CORR
2008
Springer
153views Education» more  CORR 2008»
15 years 6 months ago
Decomposition Techniques for Subgraph Matching
In the constraint programming framework, state-of-the-art static and dynamic decomposition techniques are hard to apply to problems with complete initial constraint graphs. For suc...
Stéphane Zampelli, Martin Mann, Yves Devill...
CORR
2006
Springer
127views Education» more  CORR 2006»
15 years 6 months ago
A Semidefinite Relaxation for Air Traffic Flow Scheduling
We first formulate the problem of optimally scheduling air traffic low with sector capacity constraints as a mixed integer linear program. We then use semidefinite relaxation tech...
Alexandre d'Aspremont, Laurent El Ghaoui
IJIT
2004
15 years 8 months ago
Combining ILP with Semi-supervised Learning for Web Page Categorization
This paper presents a semi-supervised learning algorithm called Iterative-Cross Training (ICT) to solve the Web pages classification problems. We apply Inductive logic programming ...
Nuanwan Soonthornphisaj, Boonserm Kijsirikul
GRID
2006
Springer
15 years 6 months ago
Simultaneous Scheduling of Replication and Computation for Data-Intensive Applications on the Grid
One of the first motivations of using grids comes from applications managing large data sets in field such as high energy physics or life sciences. To improve the global throughput...
Frederic Desprez, Antoine Vernois