[TYPES/announce] Fwd: AAAI Symposium on verification of neural networks - Expressions of Interest

[Clark Barrett]

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                                        Call For Papers
AAAI Spring Symposium on Verification of Neural Networks (VNN19)
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The 2019 AAAI Spring Symposium on Verification of Neural Networks (VNN19)
aims to bring together researchers interested in methods and tools
providing guarantees about the behaviours of neural networks and systems
built from them.  Methods based on machine learning are increasingly being
deployed for a wide range of problems, including recommender systems,
machine vision, autonomous driving, and beyond. While machine learning has
made significant contributions to such applications, concerns remain about
the lack of methods and tools to provide formal guarantees about the
behaviours of the resulting systems.  In particular, for data-driven
methods to be usable in safety-critical applications, including autonomous
systems, robotics, cybersecurity, and cyber-physical systems, it is
essential that the behaviours generated by neural networks are
well-understood and can be predicted at design time. In the case of systems
that are learning at run-time it is desirable that any change to the
underlying system respects a given safety-envelope for the system.  While
the literature on verification of traditionally designed systems is wide
and successful, there has been a lack of results and efforts in this area
until recently. The symposium intends to bring together researchers working
on a range of techniques for the verification of neural networks, ranging
from formal methods to optimisation and testing. The key objectives
include: presentation of recent work in the area; discussion of key
difficulties; collecting community benchmarks; and fostering
collaboration.  One challenge for this research this area is that results
are being published in several research communities, including formal
verification, security and privacy, systems, and AI. One of the objectives
of having a AAAI symposium is to help bridge these interdisciplinary
divides to form a cross-cutting community interested in the verification
and validation of systems based on machine learning.

The symposium workshop will include invited speakers, contributed papers,
demonstrations, breakaway sessions, and panel sessions.

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Topics of interest
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Formal specifications for neural networks and systems based on them;
SAT-based and SMT-based methods for the verification of machine learning
systems;
Mixed-integer Linear Programming methods for the verification of neural
networks;
Testing approaches to neural networks;
Optimisation-based methods for the verification of neural networks;
Statistical approaches to the verification of neural networks.

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Key Dates
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2 November 2018: Submission deadline.
3 December 2018: Acceptance notification.
14 December 2018: Registration begins.
15 February 2019: Final version of papers due.
1 March 2019: Registration deadline.
25-27 March 2019: Symposium.

For submission information and more details, see https://sites.google.com/
view/vnn19
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