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SAC
2010
ACM
13 years 3 months ago
A study on interestingness measures for associative classifiers
Associative classification is a rule-based approach to classify data relying on association rule mining by discovering associations between a set of features and a class label. Su...
Mojdeh Jalali Heravi, Osmar R. Zaïane
SIGKDD
2010
151views more  SIGKDD 2010»
13 years 3 months ago
Limitations of matrix completion via trace norm minimization
In recent years, compressive sensing attracts intensive attentions in the field of statistics, automatic control, data mining and machine learning. It assumes the sparsity of the ...
Xiaoxiao Shi, Philip S. Yu
TIFS
2010
137views more  TIFS 2010»
13 years 3 months ago
On the dynamic selection of biometric fusion algorithms
Biometric fusion consolidates the output of multiple biometric classifiers to render a decision about the identity of an individual. We consider the problem of designing a fusion s...
Mayank Vatsa, Richa Singh, Afzel Noore, Arun Ross
JMLR
2012
11 years 11 months ago
A Stick-Breaking Likelihood for Categorical Data Analysis with Latent Gaussian Models
The development of accurate models and efficient algorithms for the analysis of multivariate categorical data are important and longstanding problems in machine learning and compu...
Mohammad Emtiyaz Khan, Shakir Mohamed, Benjamin M....
JMLR
2012
11 years 11 months ago
Low rank continuous-space graphical models
Constructing tractable dependent probability distributions over structured continuous random vectors is a central problem in statistics and machine learning. It has proven diffic...
Carl Smith, Frank Wood, Liam Paninski