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JMLR
2010
163views more  JMLR 2010»
14 years 12 months ago
Dense Message Passing for Sparse Principal Component Analysis
We describe a novel inference algorithm for sparse Bayesian PCA with a zero-norm prior on the model parameters. Bayesian inference is very challenging in probabilistic models of t...
Kevin Sharp, Magnus Rattray
122
Voted
ICDAR
1999
IEEE
15 years 9 months ago
On the Evaluation of Document Analysis Components by Recall, Precision, and Accuracy
In document analysis, it is common to prove the usefulness of a component by an experimental evaluation. By applying the respective algorithms to a test sample, some effectiveness...
Markus Junker, Andreas Dengel, Rainer Hoch
UIST
2006
ACM
15 years 11 months ago
Viz: a visual analysis suite for explaining local search behavior
NP-hard combinatorial optimization problems are common in real life. Due to their intractability, local search algorithms are often used to solve such problems. Since these algori...
Steven Halim, Roland H. C. Yap, Hoong Chuin Lau
152
Voted
JMLR
2006
99views more  JMLR 2006»
15 years 5 months ago
Worst-Case Analysis of Selective Sampling for Linear Classification
A selective sampling algorithm is a learning algorithm for classification that, based on the past observed data, decides whether to ask the label of each new instance to be classi...
Nicolò Cesa-Bianchi, Claudio Gentile, Luca ...
121
Voted
SIAMMAX
2011
74views more  SIAMMAX 2011»
14 years 12 months ago
Goal-Oriented and Modular Stability Analysis
We introduce a methodology for obtaining inventories of error results for families of numerical dense linear algebra algorithms. The approach for deriving the analyses is goal-orie...
Paolo Bientinesi, Robert A. van de Geijn