ResearchTrend.AI
  • Communities
  • Connect sessions
  • AI calendar
  • Organizations
  • Join Slack
  • Contact Sales
Papers
Communities
Social Events
Terms and Conditions
Pricing
Contact Sales
Parameter LabParameter LabTwitterGitHubLinkedInBlueskyYoutube

© 2026 ResearchTrend.AI, All rights reserved.

  1. Home
  2. Papers
  3. 2010.00912
  4. Cited By
GECKO: Reconciling Privacy, Accuracy and Efficiency in Embedded Deep
  Learning
v1v2v3 (latest)

GECKO: Reconciling Privacy, Accuracy and Efficiency in Embedded Deep Learning

ACM Symposium on Applied Computing (SAC), 2020
2 October 2020
Vasisht Duddu
A. Boutet
Virat Shejwalkar
    GNN
ArXiv (abs)PDFHTML

Papers citing "GECKO: Reconciling Privacy, Accuracy and Efficiency in Embedded Deep Learning"

4 / 4 papers shown
SoK: Unintended Interactions among Machine Learning Defenses and Risks
SoK: Unintended Interactions among Machine Learning Defenses and Risks
Vasisht Duddu
S. Szyller
Nadarajah Asokan
AAML
378
6
0
07 Dec 2023
Shielding Federated Learning Systems against Inference Attacks with ARM
  TrustZone
Shielding Federated Learning Systems against Inference Attacks with ARM TrustZoneInternational Middleware Conference (Middleware), 2022
Aghiles Ait Messaoud
Sonia Ben Mokhtar
Vlad Nitu
V. Schiavoni
FedML
292
17
0
11 Aug 2022
Dikaios: Privacy Auditing of Algorithmic Fairness via Attribute Inference Attacks
Jan Aalmoes
Vasisht Duddu
A. Boutet
147
10
0
04 Feb 2022
SHAPr: An Efficient and Versatile Membership Privacy Risk Metric for
  Machine Learning
SHAPr: An Efficient and Versatile Membership Privacy Risk Metric for Machine Learning
Vasisht Duddu
S. Szyller
Nadarajah Asokan
186
16
0
04 Dec 2021
1