activity
20102020
most citedGradient Regularization for Quantization Robustness

10 citations · 21 across the 5 of their papers we have counts for

collaborators

5 papers

cs.LG202010 cited

Gradient Regularization for Quantization Robustness

Milad Alizadeh, Arash Behboodi, Mart van Baalen +3

We analyze the effect of quantizing weights and activations of neural networks on their loss and derive a simple regularization scheme that improves robustness against post-trainin…

cs.LG2018

Perturbation Analysis of Learning Algorithms: A Unifying Perspective on Generation of Adversarial Examples

Emilio Rafael Balda, Arash Behboodi, Rudolf Mathar

Despite the tremendous success of deep neural networks in various learning problems, it has been observed that adding an intentionally designed adversarial perturbation to inputs o…

cs.IT20166 cited

A Mathematical Model for Fingerprinting-based Localization Algorithms

Arash Behboodi, Filip Lemic, Adam Wolisz

A general theoretical framework for Fingerprinting Localization Algorithms (FPS), given their popularity, can be utilized for their performance studies. In this work, after setting…

cs.IT20121 cited

Selective Coding Strategy for Unicast Composite Networks

Arash Behboodi, Pablo Piantanida

Consider a composite unicast relay network where the channel statistic is randomly drawn from a set of conditional distributions indexed by a random variable, which is assumed to b…

cs.IT20104 cited

Capacity of a Class of Broadcast Relay Channels

Arash Behboodi, Pablo Piantanida

Consider the broadcast relay channel (BRC) which consists of a source sending information over a two user broadcast channel in presence of two relay nodes that help the transmissio…