Sum-product networks are a class of deep models where, surprisingly, inference remains tractable even when an arbitrary number of hidden layers are present.
Nov 11, 2016
Abstract. Inference in expressive probabilistic models is generally intractable, which makes them diffi- cult to learn and limits their applicability. Sum-.
The Sum-Product Theorem: A Foundation for Learning Tractable Models. (Supplementary Material). Abram L. Friesen. AFRIESEN@CS.WASHINGTON.EDU. Pedro Domingos.
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Abstract. Inference in expressive probabilistic models is generally intractable, which makes them diffi- cult to learn and limits their applicability. Sum-.
This paper generalizes the principle of summation to a much broader set of learning problems: all those where inference consists of summing a function over ...
Jun 19, 2016 · Sum-product networks are a class of deep models where, surprisingly, inference remains tractable even when an arbitrary number of hidden layers ...
Nov 11, 2016 · Sum-product networks are a class of deep models where, surprisingly, inference remains tractable even when an arbitrary number of hidden layers ...
... The Sum-Product Theorem: A Foundation for Learning Tractable Models Review ... Furthermore, a generic learning technique is proposed to learn the sum-product ...
Based on this, LearnSPF is able to learn tractable, high- treewidth models in any semiring. Specific choices for decomposition, clustering and leaf-creation ...