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ICDM
2009
IEEE
172views Data Mining» more  ICDM 2009»
13 years 5 months ago
Evaluating Statistical Tests for Within-Network Classifiers of Relational Data
Recently a number of modeling techniques have been developed for data mining and machine learning in relational and network domains where the instances are not independent and ide...
Jennifer Neville, Brian Gallagher, Tina Eliassi-Ra...
CORR
2010
Springer
121views Education» more  CORR 2010»
13 years 2 months ago
Deep Self-Taught Learning for Handwritten Character Recognition
Recent theoretical and empirical work in statistical machine learning has demonstrated the importance of learning algorithms for deep architectures, i.e., function classes obtaine...
Frédéric Bastien, Yoshua Bengio, Arn...
SIAMIS
2011
13 years 2 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 2 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...
PROMISE
2010
13 years 2 months ago
On the value of learning from defect dense components for software defect prediction
BACKGROUND: Defect predictors learned from static code measures can isolate code modules with a higher than usual probability of defects. AIMS: To improve those learners by focusi...
Hongyu Zhang, Adam Nelson, Tim Menzies