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NIPS
1998
13 years 11 months ago
Learning a Continuous Hidden Variable Model for Binary Data
A directed generative model for binary data using a small number of hidden continuous units is investigated. A clipping nonlinearity distinguishes the model from conventional prin...
Daniel D. Lee, Haim Sompolinsky
ML
2010
ACM
138views Machine Learning» more  ML 2010»
13 years 5 months ago
Mining adversarial patterns via regularized loss minimization
Traditional classification methods assume that the training and the test data arise from the same underlying distribution. However, in several adversarial settings, the test set is...
Wei Liu, Sanjay Chawla
WSDM
2012
ACM
301views Data Mining» more  WSDM 2012»
12 years 5 months ago
Learning evolving and emerging topics in social media: a dynamic nmf approach with temporal regularization
As massive repositories of real-time human commentary, social media platforms have arguably evolved far beyond passive facilitation of online social interactions. Rapid analysis o...
Ankan Saha, Vikas Sindhwani
EUROMICRO
1997
IEEE
14 years 2 months ago
What computer architecture can learn from computational intelligence-and vice versa
This paper considers whether the seemingly disparate fields of Computational Intelligence (CI) and computer architecture can profit from each others’ principles, results and e...
Ronald Moore, Bernd Klauer, Klaus Waldschmidt
CVPR
2010
IEEE
14 years 4 months ago
Learning 3D Action Models from a few 2D videos for View Invariant Action Recognition
Most existing approaches for learning action models work by extracting suitable low-level features and then training appropriate classifiers. Such approaches require large amount...
Pradeep Natarajan, Vivek Singh, Ram Nevatia