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Online Bayesian Shrinkage Regression.

Jamil, W. and Bouchachia, A., 2019. Online Bayesian Shrinkage Regression. In: The 27th European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning, 24--26 April 2019, Bruges, Belgium.

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ESANN2019-105.pdf - Published Version
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The present work introduces a new online regression method that extends the Shrinkage via Limit of Gibbs sampler (SLOG) in the context of online learning. In particular, we theoretically demonstrate that the proposed Online SLOG (OSLOG) is derived using the Bayesian framework without resorting to the Gibbs sampler. We also state the performance guarantee of OSLOG.

Item Type:Conference or Workshop Item (Paper)
Group:Faculty of Science & Technology
ID Code:32716
Deposited By: Symplectic RT2
Deposited On:05 Sep 2019 16:02
Last Modified:14 Mar 2022 14:17


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