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Certified Robustness to Data Poisoning in Gradient-Based Training

Certified Robustness to Data Poisoning in Gradient-Based Training

9 June 2024
Philip Sosnin
Mark N. Müller
Maximilian Baader
Calvin Tsay
Matthew Wicker
    AAML
    SILM
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Papers citing "Certified Robustness to Data Poisoning in Gradient-Based Training"

4 / 4 papers shown
Title
BNN-DP: Robustness Certification of Bayesian Neural Networks via Dynamic
  Programming
BNN-DP: Robustness Certification of Bayesian Neural Networks via Dynamic Programming
Steven Adams
A. Patané
Morteza Lahijanian
Luca Laurenti
AAML
39
7
0
19 Jun 2023
Understanding Certified Training with Interval Bound Propagation
Understanding Certified Training with Interval Bound Propagation
Yuhao Mao
Mark Niklas Muller
Marc Fischer
Martin Vechev
AAML
33
14
0
17 Jun 2023
When Deep Learning Meets Polyhedral Theory: A Survey
When Deep Learning Meets Polyhedral Theory: A Survey
Joey Huchette
Gonzalo Muñoz
Thiago Serra
Calvin Tsay
AI4CE
84
32
0
29 Apr 2023
Reluplex: An Efficient SMT Solver for Verifying Deep Neural Networks
Reluplex: An Efficient SMT Solver for Verifying Deep Neural Networks
Guy Katz
Clark W. Barrett
D. Dill
Kyle D. Julian
Mykel Kochenderfer
AAML
219
1,818
0
03 Feb 2017
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