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20192021
most citedFractal Structure and Generalization Properties of Stochastic Optimization Algorithms

10 citations · 10 across the 2 of their papers we have counts for

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stat.ML202110 cited

Fractal Structure and Generalization Properties of Stochastic Optimization Algorithms

Alexander Camuto, George Deligiannidis, Murat A. Erdogdu +3

Understanding generalization in deep learning has been one of the major challenges in statistical learning theory over the last decade. While recent work has illustrated that the d…

stat.ML2021

Asymmetric Heavy Tails and Implicit Bias in Gaussian Noise Injections

Alexander Camuto, Xiaoyu Wang, Lingjiong Zhu +3

Gaussian noise injections (GNIs) are a family of simple and widely-used regularisation methods for training neural networks, where one injects additive or multiplicative Gaussian n…

stat.ML2020

Explicit Regularisation in Gaussian Noise Injections

Alexander Camuto, Matthew Willetts, Umut Şimşekli +2

We study the regularisation induced in neural networks by Gaussian noise injections (GNIs). Though such injections have been extensively studied when applied to data, there have be…

stat.ML2020

Towards a Theoretical Understanding of the Robustness of Variational Autoencoders

Alexander Camuto, Matthew Willetts, Stephen Roberts +2

We make inroads into understanding the robustness of Variational Autoencoders (VAEs) to adversarial attacks and other input perturbations. While previous work has developed algorit…

stat.ML2019

Improving VAEs' Robustness to Adversarial Attack

Matthew Willetts, Alexander Camuto, Tom Rainforth +2

Variational autoencoders (VAEs) have recently been shown to be vulnerable to adversarial attacks, wherein they are fooled into reconstructing a chosen target image. However, how to…