26 citations · 35 across the 10 of their papers we have counts for
5 papers · 1 filter
Generalization Properties of Adversarial Training for -Bounded Adversarial Attacks
Payam Delgosha, Hamed Hassani, Ramtin Pedarsani
We have widely observed that neural networks are vulnerable to small additive perturbations to the input causing misclassification. In this paper, we focus on the -bounded…
Binary Classification Under Attacks for General Noise Distribution
Payam Delgosha, Hamed Hassani, Ramtin Pedarsani
Adversarial examples have recently drawn considerable attention in the field of machine learning due to the fact that small perturbations in the data can result in major performanc…
Efficient and Robust Classification for Sparse Attacks
Mark Beliaev, Payam Delgosha, Hamed Hassani +1
In the past two decades we have seen the popularity of neural networks increase in conjunction with their classification accuracy. Parallel to this, we have also witnessed how frag…
Robust Classification Under Attack for the Gaussian Mixture Model
Payam Delgosha, Hamed Hassani, Ramtin Pedarsani
It is well-known that machine learning models are vulnerable to small but cleverly-designed adversarial perturbations that can cause misclassification. While there has been major p…
Deep Switch Networks for Generating Discrete Data and Language
Payam Delgosha, Naveen Goela
Multilayer switch networks are proposed as artificial generators of high-dimensional discrete data (e.g., binary vectors, categorical data, natural language, network log files, and…