3 citations · 7 across the 6 of their papers we have counts for
7 papers
Weightless Neural Networks for Efficient Edge Inference
Zachary Susskind, Aman Arora, Igor Dantas Dos Santos Miranda +8
Weightless Neural Networks (WNNs) are a class of machine learning model which use table lookups to perform inference. This is in contrast with Deep Neural Networks (DNNs), which us…
wisardpkg -- A library for WiSARD-based models
Aluizio S. Lima Filho, Gabriel P. Guarisa, Leopoldo A. D. Lusquino Filho +3
In order to facilitate the production of codes using WiSARD-based models, LabZero developed an ML library C++/Python called wisardpkg. This library is an MIT-licensed open-source p…
Exploring the Equivalence between Dynamic Dataflow Model and Gamma - General Abstract Model for Multiset mAnipulation
Rui R. Mello Junior, Leandro S. Araujo, Tiago A. O. Alves +3
With the increase of the search for computational models where the expression of parallelism occurs naturally, some paradigms arise as options for the next generation of computers.…
Decanting the Contribution of Instruction Types and Loop Structures in the Reuse of Traces
Andrey M. Coppieters, Sheila de Oliveira, Felipe M. G. França +2
Reuse has been proposed as a microarchitecture-level mechanism to reduce the amount of executed instructions, collapsing dependencies and freeing resources for other instructions.…
RAdNet-VE: An Interest-Centric Mobile Ad Hoc Network for Vehicular Environments
F. B. Gonçalves, F. M. G. França, C. L. Amorim
In this study, we propose a variation of the RAdNet for vehicular environments (RAdNet-VE). The proposed scheme extends the message header, mechanism for registering interest, and…
Couillard: Parallel Programming via Coarse-Grained Data-Flow Compilation
Leandro A. J. Marzulo, Tiago A. O. Alves, Felipe M. G. França +1
Data-flow is a natural approach to parallelism. However, describing dependencies and control between fine-grained data-flow tasks can be complex and present unwanted overheads. TAL…