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SIAMIS
2011
13 years 4 months ago
Large Scale Bayesian Inference and Experimental Design for Sparse Linear Models
Abstract. Many problems of low-level computer vision and image processing, such as denoising, deconvolution, tomographic reconstruction or superresolution, can be addressed by maxi...
Matthias W. Seeger, Hannes Nickisch
IHI
2010
197views Healthcare» more  IHI 2010»
13 years 4 months ago
Beyond safe harbor: automatic discovery of health information de-identification policy alternatives
Regulations in various countries permit the reuse of health information without patient authorization provided the data is "de-identified". In the United States, for ins...
Kathleen Benitez, Grigorios Loukides, Bradley Mali...
JMLR
2010
179views more  JMLR 2010»
13 years 4 months ago
PAC-Bayesian Analysis of Co-clustering and Beyond
We derive PAC-Bayesian generalization bounds for supervised and unsupervised learning models based on clustering, such as co-clustering, matrix tri-factorization, graphical models...
Yevgeny Seldin, Naftali Tishby
SADM
2010
141views more  SADM 2010»
13 years 4 months ago
A parametric mixture model for clustering multivariate binary data
: The traditional latent class analysis (LCA) uses a mixture model with binary responses on each subject that are independent conditional on cluster membership. However, in many pr...
Ajit C. Tamhane, Dingxi Qiu, Bruce E. Ankenman
TNN
2010
234views Management» more  TNN 2010»
13 years 4 months ago
Novel maximum-margin training algorithms for supervised neural networks
This paper proposes three novel training methods, two of them based on the back-propagation approach and a third one based on information theory for Multilayer Perceptron (MLP) bin...
Oswaldo Ludwig, Urbano Nunes