Towards Reliable AI via Efficient Verification of Binarized Neural Networks
Deep neural networks have achieved great success on many tasks and even surpass human performance in certain settings. Despite this success, neural networks are known to be vulnerable to the problem of adversarial inputs, where small and human- imperceptible changes in the input cause large and unex...
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Massachusetts Institute of Technology
2022
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| Online Access: | https://hdl.handle.net/1721.1/138993 https://orcid.org/0000-0001-8215-9899 |