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Algorithms for Verifying Deep Neural Networks (Paperback)
Loot Price: R2,223
Discovery Miles 22 230
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Algorithms for Verifying Deep Neural Networks (Paperback)
Series: Foundations and Trends (R) in Optimization
Expected to ship within 10 - 15 working days
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Total price: R2,243
Discovery Miles: 22 430
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Neural networks have been widely used in many applications, such as
image classification and understanding, language processing, and
control of autonomous systems. These networks work by mapping
inputs to outputs through a sequence of layers. At each layer, the
input to that layer undergoes an affine transformation followed by
a simple nonlinear transformation before being passed to the next
layer. Neural networks are being used for increasingly important
tasks, and in some cases, incorrect outputs can lead to costly
consequences, hence validation of correctness at each layer is
vital. The sheer size of the networks makes this not feasible using
traditional methods. In this monograph, the authors survey a class
of methods that are capable of formally verifying properties of
deep neural networks. In doing so, they introduce a unified
mathematical framework for verifying neural networks, classify
existing methods under this framework, provide pedagogical
implementations of existing methods, and compare those methods on a
set of benchmark problems. Algorithms for Verifying Deep Neural
Networks serves as a tutorial for students and professionals
interested in this emerging field as well as a benchmark to
facilitate the design of new verification algorithms.
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