國立高雄大學圖資館 |

Language: English

Back

Software verification and formal methods for ML-enabled autonomous systems5th International Workshop, FoMLAS 2022, and 15th International Workshop, NSV 2022, Haifa, Israel, July 31 - August 1, and August 11, 2022 : proceedings /

Record Type:	Electronic resources : Monograph/item
Title/Author:	Software verification and formal methods for ML-enabled autonomous systemsedited by Omri Isac ... [et al.].
Reminder of title:	5th International Workshop, FoMLAS 2022, and 15th International Workshop, NSV 2022, Haifa, Israel, July 31 - August 1, and August 11, 2022 : proceedings /
remainder title:	FoMLAS 2022
other author:	Isac, Omri.
corporate name:
Published:	Cham :Springer International Publishing :2022.
Description:	x, 205 p. :ill., digital ;24 cm.
Contained By:	Springer Nature eBook
Subject:	Computer softwareCongresses.Verification
Online resource:	https://doi.org/10.1007/978-3-031-21222-2
ISBN:	9783031212222$q(electronic bk.)

Software verification and formal methods for ML-enabled autonomous systems5th International Workshop, FoMLAS 2022, and 15th International Workshop, NSV 2022, Haifa, Israel, July 31 - August 1, and August 11, 2022 : proceedings /
Software verification and formal methods for ML-enabled autonomous systems5th International Workshop, FoMLAS 2022, and 15th International Workshop, NSV 2022, Haifa, Israel, July 31 - August 1, and August 11, 2022 : proceedings /[electronic resource] :FoMLAS 2022edited by Omri Isac ... [et al.]. - Cham :Springer International Publishing :2022. - x, 205 p. :ill., digital ;24 cm. - Lecture notes in computer science,134660302-9743 ;. - Lecture notes in computer science ;4891..

FoMLAS 2022 -- VPN: Verification of Poisoning in Neural Networks -- A Cascade of Checkers for Run-time Certification of Local Robustness -- CEG4N: Counter-Example Guided Neural Network Quantization Refinement -- Minimal Multi-Layer Modifications of Deep Neural Networks -- Differentiable Logics for Neural Network Training and Verification -- Neural Networks in Imandra: Matrix Representation as a Verification Choice -- Self-Correcting Neural Networks For Safe Classification -- Self-Correcting Neural Networks For Safe Classification -- NSV 2022 -- Verified Numerical Methods for Ordinary Differential Equations -- Neural Network Precision Tuning Using Stochastic Arithmetic -- MLTL Multi-type (MLTLM): A Logic for Reasoning about Signals of Different Types.

This book constitutes the refereed proceedings of the 5th International Workshop on Software Verification and Formal Methods for ML-Enables Autonomous Systems, FoMLAS 2022, and the 15th International Workshop on Numerical Software Verification, NSV 2022, which took place in Haifa, Israel, in July/August 2022. The volume contains 8 full papers from the FoMLAS 2022 workshop and 3 full papers from the NSV 2022 workshop. The FoMLAS workshop is dedicated to the development of novel formal methods techniques to discussing on how formal methods can be used to increase predictability, explainability, and accountability of ML-enabled autonomous systems. NSV 2022 is focusing on the challenges of the verification of cyber-physical systems with machine learning components.

ISBN: 9783031212222$q(electronic bk.)

Standard No.: 10.1007/978-3-031-21222-2doiSubjects--Topical Terms:

443711
Computer software
--Verification--Congresses.

LC Class. No.: QA76.76.V47

Dewey Class. No.: 005.14

Software verification and formal methods for ML-enabled autonomous systems5th International Workshop, FoMLAS 2022, and 15th International Workshop, NSV 2022, Haifa, Israel, July 31 - August 1, and August 11, 2022 : proceedings /
LDR:02813nmm a2200361 a 4500 001 633947
003 DE-He213
005 20221215094755.0
006 m d
007 cr nn 008maaau
008 230511s2022 sz s 0 eng d
020 $a 9783031212222$q(electronic bk.)
020 $a 9783031212215$q(paper)
024 7 $a 10.1007/978-3-031-21222-2 $2 doi
035 $a 978-3-031-21222-2
040 $a GP $c GP
041 0 $a eng
050 4 $a QA76.76.V47
072 7 $a UYA $2 bicssc
072 7 $a COM051000 $2 bisacsh
072 7 $a UYA $2 thema
082 0 4 $a 005.14 $2 23
090 $a QA76.76.V47 $b I61 2022
111 2 $n (3rd : $d 1998 : $c Amsterdam, Netherlands) $3 194767
245 1 0 $a Software verification and formal methods for ML-enabled autonomous systems $h [electronic resource] : $b 5th International Workshop, FoMLAS 2022, and 15th International Workshop, NSV 2022, Haifa, Israel, July 31 - August 1, and August 11, 2022 : proceedings / $c edited by Omri Isac ... [et al.].
246 3 $a FoMLAS 2022
246 3 $a NSV 2022
260 $a Cham : $b Springer International Publishing : $b Imprint: Springer, $c 2022.
300 $a x, 205 p. : $b ill., digital ; $c 24 cm.
490 1 $a Lecture notes in computer science, $x 0302-9743 ; $v 13466
505 0 $a FoMLAS 2022 -- VPN: Verification of Poisoning in Neural Networks -- A Cascade of Checkers for Run-time Certification of Local Robustness -- CEG4N: Counter-Example Guided Neural Network Quantization Refinement -- Minimal Multi-Layer Modifications of Deep Neural Networks -- Differentiable Logics for Neural Network Training and Verification -- Neural Networks in Imandra: Matrix Representation as a Verification Choice -- Self-Correcting Neural Networks For Safe Classification -- Self-Correcting Neural Networks For Safe Classification -- NSV 2022 -- Verified Numerical Methods for Ordinary Differential Equations -- Neural Network Precision Tuning Using Stochastic Arithmetic -- MLTL Multi-type (MLTLM): A Logic for Reasoning about Signals of Different Types.
520 $a This book constitutes the refereed proceedings of the 5th International Workshop on Software Verification and Formal Methods for ML-Enables Autonomous Systems, FoMLAS 2022, and the 15th International Workshop on Numerical Software Verification, NSV 2022, which took place in Haifa, Israel, in July/August 2022. The volume contains 8 full papers from the FoMLAS 2022 workshop and 3 full papers from the NSV 2022 workshop. The FoMLAS workshop is dedicated to the development of novel formal methods techniques to discussing on how formal methods can be used to increase predictability, explainability, and accountability of ML-enabled autonomous systems. NSV 2022 is focusing on the challenges of the verification of cyber-physical systems with machine learning components.
650 0 $a Computer software $x Verification $v Congresses. $3 443711
650 0 $a Software engineering $3 253562
650 0 $a Formal methods (Computer science) $3 277520
650 0 $a Machine learning $v Congresses. $3 384498
700 1 $a Isac, Omri. $3 940070
710 2 $a SpringerLink (Online service) $3 273601
711 2 $n (3rd : $d 1998 : $c Amsterdam, Netherlands) $3 194767
773 0 $t Springer Nature eBook
830 0 $a Lecture notes in computer science ; $v 4891. $3 383229
856 4 0 $u https://doi.org/10.1007/978-3-031-21222-2
950 $a Computer Science (SpringerNature-11645)