activity
20152019
most citedTransferable Clean-Label Poisoning Attacks on Deep Neural Nets

137 citations · 269 across the 8 of their papers we have counts for

collaborators

12 papers

cs.LG201917 cited

Adversarial attacks on Copyright Detection Systems

Parsa Saadatpanah, Ali Shafahi, Tom Goldstein

It is well-known that many machine learning models are susceptible to adversarial attacks, in which an attacker evades a classifier by making small perturbations to inputs. This pa…

stat.ML2019137 cited

Transferable Clean-Label Poisoning Attacks on Deep Neural Nets

Chen Zhu, W. Ronny Huang, Ali Shafahi +4

Clean-label poisoning attacks inject innocuous looking (and "correctly" labeled) poison images into training data, causing a model to misclassify a targeted image after being train…

math.OC2017

PhasePack: A Phase Retrieval Library

Rohan Chandra, Ziyuan Zhong, Justin Hontz +3

Phase retrieval deals with the estimation of complex-valued signals solely from the magnitudes of linear measurements. While there has been a recent explosion in the development of…

cs.MS2017

PhasePack User Guide

Rohan Chandra, Ziyuan Zhong, Justin Hontz +3

"Phase retrieval" refers to the recovery of signals from the magnitudes (and not the phases) of linear measurements. While there has been a recent explosion in development of phase…

cs.IT2017

VLSI Designs for Joint Channel Estimation and Data Detection in Large SIMO Wireless Systems

Oscar Castañeda, Tom Goldstein, Christoph Studer

Channel estimation errors have a critical impact on the reliability of wireless communication systems. While virtually all existing wireless receivers separate channel estimation f…

cs.LG201794 cited

Training Quantized Nets: A Deeper Understanding

Hao Li, Soham De, Zheng Xu +3

Currently, deep neural networks are deployed on low-power portable devices by first training a full-precision model using powerful hardware, and then deriving a corresponding low-p…