A Mixed Integer Programming Approach for Verifying Properties of
Binarized Neural Networks

A Mixed Integer Programming Approach for Verifying Properties of Binarized Neural Networks

11 March 2022

Christopher Lazarus

Mykel J. Kochenderfer

Papers citing "A Mixed Integer Programming Approach for Verifying Properties of Binarized Neural Networks"

7 / 7 papers shown

Title
Verifying Properties of Binary Neural Networks Using Sparse Polynomial Optimization Jianting Yang Srecko Ðurasinovic Jean B. Lasserre Victor Magron Jun Zhao AAML 39 1 0 27 May 2024
Verification of Neural Networks Local Differential Classification Privacy Roie Reshef Anan Kabaha Olga Seleznova Dana Drachsler-Cohen AAML 21 2 0 31 Oct 2023
Quantization-aware Interval Bound Propagation for Training Certifiably Robust Quantized Neural Networks Mathias Lechner Dorde Zikelic K. Chatterjee T. Henzinger Daniela Rus AAML 16 2 0 29 Nov 2022
Deep Binary Reinforcement Learning for Scalable Verification Christopher Lazarus Mykel J. Kochenderfer OffRL 42 0 0 11 Mar 2022
Efficient and Robust Mixed-Integer Optimization Methods for Training Binarized Deep Neural Networks Jannis Kurtz B. Bah MQ 21 4 0 21 Oct 2021
Exploiting Verified Neural Networks via Floating Point Numerical Error Kai Jia Martin Rinard AAML 37 34 0 06 Mar 2020
Reluplex: An Efficient SMT Solver for Verifying Deep Neural Networks Guy Katz Clark W. Barrett D. Dill Kyle D. Julian Mykel Kochenderfer AAML 231 1,837 0 03 Feb 2017