Denoised Smoothing

Denoised Smoothing

When it comes to machine learning, having a strong classifier is crucial for making accurate predictions. However, sometimes even the best pretrained classifiers can falter when faced with unexpected inputs or noise. This is where denoised smoothing comes in, as it offers a method for enhancing an existing classifier without the need for more training or adjustments. What is Denoised Smoothing? Denoised smoothing is a process that allows a user to improve an existing classifier's performance

Fishr

Fishr

Introduction to Fishr Fishr is a learning scheme that is used to enforce domain invariance in the space of gradients of the loss function. This is achieved by introducing a regularization term to match the domain-level variances of gradients across training domains. Fishr exhibits close relations with the Fisher Information and the Hessian of the loss. By forcing domain-level gradient covariances to be similar during the learning procedure, the domain-level loss landscapes are eventually aligne

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