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Mixed-Privacy Forgetting in Deep Networks
We show that the influence of a subset of the training samples can be re...
12/24/2020 ∙ by Aditya Golatkar, et al. ∙
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LQF: Linear Quadratic Fine-Tuning
Classifiers that are linear in their parameters, and trained by optimizi...
12/21/2020 ∙ by Alessandro Achille, et al. ∙
8
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Forgetting Outside the Box: Scrubbing Deep Networks of Information Accessible from Input-Output Observations
We describe a procedure for removing dependency on a cohort of training ...
03/05/2020 ∙ by Aditya Golatkar, et al. ∙
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Eternal Sunshine of the Spotless Net: Selective Forgetting in Deep Neural Networks
We explore the problem of selectively forgetting a particular set of dat...
11/12/2019 ∙ by Aditya Golatkar, et al. ∙
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Eternal Sunshine of the Spotless Net: Selective Forgetting in Deep Networks
We explore the problem of selectively forgetting a particular set of dat...
11/12/2019 ∙ by Aditya Golatkar, et al. ∙
16
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Time Matters in Regularizing Deep Networks: Weight Decay and Data Augmentation Affect Early Learning Dynamics, Matter Little Near Convergence
Regularization is typically understood as improving generalization by al...
05/30/2019 ∙ by Aditya Golatkar, et al. ∙
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Sparse Kernel PCA for Outlier Detection
In this paper, we propose a new method to perform Sparse Kernel Principa...
09/07/2018 ∙ by Rudrajit Das, et al. ∙
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Classification of Breast Cancer Histology using Deep Learning
Breast Cancer is a major cause of death worldwide among women. Hematoxyl...
02/22/2018 ∙ by Aditya Golatkar, et al. ∙
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