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cs.LG2020★ 2 cited
Investigating the Compositional Structure Of Deep Neural Networks
Francesco Craighero, Fabrizio Angaroni, Alex Graudenzi +2
The current understanding of deep neural networks can only partially explain how input structure, network parameters and optimization algorithms jointly contribute to achieve the s…
cs.LG2017
Efficient computational strategies to learn the structure of probabilistic graphical models of cumulative phenomena
Daniele Ramazzotti, Marco S. Nobile, Marco Antoniotti +1
Structural learning of Bayesian Networks (BNs) is a NP-hard problem, which is further complicated by many theoretical issues, such as the I-equivalence among different structures.…