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An Efficient Algorithm for Representing Piecewise Linear Functions into Logic

  • Published:2020-09 Issue: Volume:351 Page:167-186
  • ISSN:1571-0661
  • Container-title:Electronic Notes in Theoretical Computer Science
  • language:en
  • Short-container-title:Electronic Notes in Theoretical Computer Science

Author:

Preto Sandro,Finger Marcelo

Funder

CAPES

CNPq

Publisher

Elsevier BV

Subject

General Computer Science,Theoretical Computer Science

Reference18 articles.

1. The complexity of McNaughton functions of one variable;Aguzzoli;Advances in Applied Mathematics,1998

2. Weierstrass approximations by Łukasiewicz formulas with one quantified variable;Aguzzoli,2001

3. Weierstrass Approximation Theorem and Łukasiewicz Formulas with one Quantified Variable;Aguzzoli,2003

4. Neural networks and rational Łukasiewicz logic;Amato,2002

5. An algorithm for the automatic generation of a logical formula representing a control law;Amato;Neural Network World,2000

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1. Logical Approximation and Formal Verification of Neural Networks;Anais do V Workshop Brasileiro de Lógica (WBL 2024);2024-07-21

2. Chapter 28. Effective Reasoning over Neural Networks Using Łukasiewicz Logic;Frontiers in Artificial Intelligence and Applications;2023-07-21

3. Benchmarking Łukasiewicz Logic Solvers with Properties of Neural Networks;2023 IEEE 53rd International Symposium on Multiple-Valued Logic (ISMVL);2023-05

4. Proving properties of binary classification neural networks via Łukasiewicz logic;Logic Journal of the IGPL;2022-06-10

5. Efficient representation of piecewise linear functions into Łukasiewicz logic modulo satisfiability;Mathematical Structures in Computer Science;2022-05-17
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