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Supervising topic models with Gaussian processes
(Elsevier, 2018-05)
Topic modeling is a powerful approach for modeling data represented as high-dimensional histograms. While the high dimensionality of such input data is extremely beneficial in unsupervised applications including language ...
Variational closed-Form deep neural net inference
(Elsevier, 2018-09)
We introduce a Bayesian construction for deep neural networks that is amenable to mean field variational inference that operates solely by closed-form update rules. Hence, it does not require any learning rate to be manually ...
On context-aware DDoS attacks using deep generative networks
(IEEE, 2018-10)
Distributed Denial of Service (DDoS) attacks continue to be one of the most severe threats in the Internet. The intrinsic challenge in preventing DDoS attacks is to distinguish them from legitimate flash crowds since two ...
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