Nicolas Papernot

Nicolas Papernot

Research Areas

Authored Publications
0 results

Sort By
  • Title
  • Title, descending
  • Year
  • Year, descending
    Google
Thieves of Sesame Street: Model Extraction on BERT-based APIs
Kalpesh Krishna
Gaurav Singh Tomar
Ankur Parikh
Nicolas Papernot
Mohit Iyyer
ICLR 2020 (2020)
Analyzing and Improving Representations with the Soft Nearest Neighbor Loss
Nicholas Frosst
Nicolas Papernot
Geoffrey Hinton
ICML (2019) (to appear)
Improving Differentially Private Models with Active Learning
Zhengli Zhao
Nicolas Papernot
Sameer Singh
Neoklis Polyzotis
Augustus Odena
arXiv preprint arXiv:1910.01177 (2019)
MixMatch: A Holistic Approach to Semi-Supervised Learning
David Berthelot
Nicholas Carlini
Ian Goodfellow
Nicolas Papernot
Avital Oliver
Colin Raffel
NeurIPS (2019) (to appear)
Scalable Private Learning with PATE
Nicolas Papernot
Shuang Song
Ilya Mironov
Ananth Raghunathan
Kunal Talwar
Úlfar Erlingsson
International Conference on Learning Representations (ICLR) (2018)
Ensemble Adversarial Training: Attacks and Defenses
Alex Kurakin
Dan Boneh
Florian Tramèr
Ian Goodfellow
Nicolas Papernot
Patrick McDaniel
ICLR (2018)
A General Approach to Adding Differential Privacy to Iterative Training Procedures
Brendan McMahan
Galen Andrew
Ilya Mironov
Nicolas Papernot
Peter Kairouz
Steve Chien
Úlfar Erlingsson
NIPS (2018)
Adversarial Examples that Fool both Computer Vision and Time-Limited Humans
Gamaleldin Fathy Elsayed
Shreya Shankar
Brian Cheung
Nicolas Papernot
Alex Kurakin
Ian Goodfellow
Jascha Sohl-dickstein
NeurIPS (2018)
The Space of Transferable Adversarial Examples
Florian Tramèr
Nicolas Papernot
Ian Goodfellow
Dan Boneh
Patrick McDaniel
arXiv (2017)
Adversarial Attacks on Neural Network Policies
Sandy Huang
Nicolas Papernot
Ian Goodfellow
Yan Duan
Pieter Abbeel
arXiv (2017)
Search on Google Scholar