Oct 14, 2024 · In the area of adversarial machine learning, disrupting generalization with cleanly labeled training examples is known as clean-label poisoning.

In the area of adversarial machine learning, disrupting generalization with cleanly labeled training examples is known as clean-label poisoning.

Neural networks are powered by an implicit bias: a tendency of gradient descent to fit training data in a way that generalizes to unseen data.

Oct 24, 2024 · In the area of adversarial machine learning, disrupting generalization with cleanly labeled training examples is known as clean-label poisoning.

Oct 17, 2024 · This failure occurs despite the special training examples being labeled by the teacher, i.e. having clean labels! We empirically demonstrate the ...

It is proved that while implicit bias leads to generalization under many choices of training data, there exist special examples whose inclusion in training ...

In the area of adversarial machine learning, disrupting generalization with cleanly labeled training examples is known as clean-label poisoning. Given the ...

Oct 24, 2024 · This failure to generalize, even with clean training data, is known as "clean-label poisoning" in the field of adversarial machine learning.

Oct 26, 2024 · The Implicit Bias of Structured State Space Models Can Be Poisoned With Clean Labels. https://t.co/7PTr42eXTE.

Official implementation for the experiments in The Implicit Bias of Structured State Space Models Can Be Poisoned With Clean Labels, based on the Tensorflow, ...