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| Titel: |
Challenging SMT solvers to verify neural networks |
| Auteur: |
Pulina, Luca Tacchella, Armando |
| Verschenen in: |
AI communications |
| Paginering: | Jaargang 25 (2012) nr. 2 pagina's 117-135 |
| Jaar: |
2012-07-24 |
| Inhoud: |
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. |
| Uitgever: |
IOS Press |
| Bronbestand: |
Elektronische Wetenschappelijke Tijdschriften |
Details van artikel 3 van 16 gevonden artikelen
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