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CORR
2010
Springer
207views Education» more  CORR 2010»
13 years 7 months ago
Collaborative Hierarchical Sparse Modeling
Sparse modeling is a powerful framework for data analysis and processing. Traditionally, encoding in this framework is performed by solving an 1-regularized linear regression prob...
Pablo Sprechmann, Ignacio Ramírez, Guillerm...
CSDA
2007
87views more  CSDA 2007»
13 years 7 months ago
Estimation and inference in functional mixed-effects models
Functional mixed-effects models are very useful in analyzing functional data. A general functional mixed-effects model that inherits the flexibility of linear mixed-effects model...
Anestis Antoniadis, Theofanis Sapatinas
BMCBI
2007
154views more  BMCBI 2007»
13 years 7 months ago
Inferring biological networks with output kernel trees
Background: Elucidating biological networks between proteins appears nowadays as one of the most important challenges in systems biology. Computational approaches to this problem ...
Pierre Geurts, Nizar Touleimat, Marie Dutreix, Flo...
KDD
2009
ACM
210views Data Mining» more  KDD 2009»
14 years 8 months ago
Large-scale behavioral targeting
Behavioral targeting (BT) leverages historical user behavior to select the ads most relevant to users to display. The state-of-the-art of BT derives a linear Poisson regression mo...
Ye Chen, Dmitry Pavlov, John F. Canny
KDD
2007
ACM
209views Data Mining» more  KDD 2007»
14 years 8 months ago
Temporal causal modeling with graphical granger methods
The need for mining causality, beyond mere statistical correlations, for real world problems has been recognized widely. Many of these applications naturally involve temporal data...
Andrew Arnold, Yan Liu, Naoki Abe