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» Learning Monotonic Linear Functions
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NIPS
2007
13 years 11 months ago
Hierarchical Penalization
Hierarchical penalization is a generic framework for incorporating prior information in the fitting of statistical models, when the explicative variables are organized in a hiera...
Marie Szafranski, Yves Grandvalet, Pierre Morizet-...
COMPGEOM
2009
ACM
14 years 4 months ago
Cache-oblivious range reporting with optimal queries requires superlinear space
We consider a number of range reporting problems in two and three dimensions and prove lower bounds on the amount of space used by any cache-oblivious data structure for these pro...
Peyman Afshani, Chris H. Hamilton, Norbert Zeh
BMCBI
2008
129views more  BMCBI 2008»
13 years 10 months ago
Gene set enrichment analysis for non-monotone association and multiple experimental categories
Background: Recently, microarray data analyses using functional pathway information, e.g., gene set enrichment analysis (GSEA) and significance analysis of function and expression...
Rongheng Lin, Shuangshuang Dai, Richard D. Irwin, ...
TKDE
2010
274views more  TKDE 2010»
13 years 8 months ago
Ranked Query Processing in Uncertain Databases
—Recently, many new applications, such as sensor data monitoring and mobile device tracking, raise up the issue of uncertain data management. Compared to “certain” data, the ...
Xiang Lian, Lei Chen 0002
CORR
2010
Springer
92views Education» more  CORR 2010»
13 years 7 months ago
Regression on fixed-rank positive semidefinite matrices: a Riemannian approach
The paper addresses the problem of learning a regression model parameterized by a fixed-rank positive semidefinite matrix. The focus is on the nonlinear nature of the search space...
Gilles Meyer, Silvere Bonnabel, Rodolphe Sepulchre