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Details for article 3 of 16 found articles
| Title: |
Challenging SMT solvers to verify neural networks |
| Author: |
Pulina, Luca Tacchella, Armando |
| Appeared in: |
AI communications |
| Paging: | Volume 25 (2012) nr. 2 pages 117-135 |
| Year: |
2012-07-24 |
| Contents: |
In recent years, Satisfiability Modulo Theory (SMT) solvers are becoming increasingly popular in the Computer Aided Verification and Reasoning community. Used natively or as back-engines, they are accumulating a record of success stories and, as witnessed by the annual SMT competition, their performances and capacity are also increasing steadily. Introduced in previous contributions of ours, a new application domain providing an outstanding challenge for SMT solvers is represented by verification of Multi-Layer Perceptrons (MLPs) a widely-adopted kind of artificial neural network. In this paper we present an extensive evaluation of the current state-of-the-art SMT solvers and assess their potential in the promising domain of MLP verification. |
| Publisher: |
IOS Press |
| Source file: |
Elektronische Wetenschappelijke Tijdschriften |
Details for article 3 of 16 found articles
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