The lattice overparametrization paradigm for the machine learning of lattice operators
D Marcondes, J Barrera - International Conference on Discrete Geometry …, 2024 - Springer
The machine learning of lattice operators has three possible bottlenecks. From a statistical
standpoint, it is necessary to design a constrained class of operators based on prior …
standpoint, it is necessary to design a constrained class of operators based on prior …
An Algorithm to Train Unrestricted Sequential Discrete Morphological Neural Networks
D Marcondes, M Feldman, J Barrera - International Conference on Discrete …, 2024 - Springer
There have been attempts to insert mathematical morphology (MM) operators into
convolutional neural networks (CNN), and the most successful endeavor to date has been …
convolutional neural networks (CNN), and the most successful endeavor to date has been …
Unrestricted Sequential Discrete Morphological Neural Networks
D Marcondes, M Feldman, J Barrera - 2024 - researchsquare.com
There have been attempts to insert mathematical morphology (MM) operators into
convolutional neural networks (CNN), and the most successful endeavor to date has been …
convolutional neural networks (CNN), and the most successful endeavor to date has been …
Learning W-operators in the boolean interval partition lattice learning space
FE Cunha Filho - 2024 - teses.usp.br
This work presents the Stochastic Descent on the Boolean Interval Partition Lattice (SDBIPL)
algorithm, a novel contribution to the field of lattice-based learning. The SDBIPL algorithm …
algorithm, a novel contribution to the field of lattice-based learning. The SDBIPL algorithm …