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M. Sinn

20 papers hereh-index 192.1k citations63 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • first author3
  • middle author13
  • last author4

Across the 20 of 20 papers where every author was matched, so the position is known.

fields
  • cs.LG7
  • cs.AI3
  • cs.CR2
  • stat.ML2
  • cs.CV1
  • cs.DB1

identity via Semantic Scholar / OpenAlex

activity
20082022
most citedIBM Federated Learning: an Enterprise Framework White Paper V0.1

112 citations · 320 across the 20 of their papers we have counts for

collaborators
Showing 2021Show all

4 papers · 1 filter

cs.LG2021★ 2 cited

Certified Federated Adversarial Training

Giulio Zizzo, Ambrish Rawat, Mathieu Sinn +2

In federated learning (FL), robust aggregation schemes have been developed to protect against malicious clients. Many robust aggregation schemes rely on certain numbers of benign c…

cs.LG2021

Automated Robustness with Adversarial Training as a Post-Processing Step

Ambrish Rawat, Mathieu Sinn, Beat Buesser

Adversarial training is a computationally expensive task and hence searching for neural network architectures with robustness as the criterion can be challenging. As a step towards…

cs.CR2021

DLPFS: The Data Leakage Prevention FileSystem

Stefano Braghin, Marco Simioni, Mathieu Sinn

Shared folders are still a common practice for granting third parties access to data files, regardless of the advances in data sharing technologies. Services like Google Drive, Dro…

cs.CR2021

The Devil is in the GAN: Backdoor Attacks and Defenses in Deep Generative Models

Ambrish Rawat, Killian Levacher, Mathieu Sinn

Deep Generative Models (DGMs) are a popular class of deep learning models which find widespread use because of their ability to synthesize data from complex, high-dimensional manif…

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Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.