Online Structure Learning for Feed-Forward and Recurrent Sum-Product Networks

Abdullah Rashwan
Abdullah Rashwan
Wei-Shou Hsu
Wei-Shou Hsu
Georgios Trimponias
Georgios Trimponias

ADVANCES IN NEURAL INFORMATION PROCESSING SYSTEMS 31 (NIPS 2018), pp. 6944-6954, 2018.

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Abstract:

Sum-product networks have recently emerged as an attractive representation due to their dual view as a special type of deep neural network with clear semantics and a special type of probabilistic graphical model for which marginal inference is always tractable. These properties follow from the conditions of completeness and decomposabilit...More

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