Jun 28, 2021 · Abstract:We consider the problem of finding optimal classifiers in an adversarial setting where the class-1 data is generated by an attacker ...
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Oct 31, 2021 · We propose a Bayesian game framework where the defender chooses a classifier with no a priori restriction on the set of possible classifiers.
We consider the problem of finding optimal classifiers in an adversarial setting where the class-1 data is generated by an attacker whose objective is not ...
We consider the problem of finding optimal classifiers in an adversarial setting where the class-1 data is generated by an attacker whose objective is not ...
We consider the problem of finding optimal classifiers in an adversarial setting where the class-1 data is generated by an attacker whose objective is not ...
We consider the problem of finding optimal classifiers in an adversarial setting where the class-1 data is generated by an attacker whose objective is not ...
We consider the problem of finding optimal classifiers in an adversarial setting where the class-1 data is generated by an attacker whose objective is not ...
Jun 28, 2021 · This repository is the official implementation of the paper "Scalable optimal classifiers for adversarial settings under uncertainty".
This work proposes to embed machine learning within a game theoretic framework that performs adversarial modeling, develops methods for optimizing ...
Online Prediction Problems with Variation. Chapter © 2014. Scalable Optimal Classifiers for Adversarial Settings Under Uncertainty. Chapter © 2021. References.