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Confidential Boosting with Random Linear Classifiers for Outsourced
  User-generated Data
v1v2v3v4 (latest)

Confidential Boosting with Random Linear Classifiers for Outsourced User-generated Data

22 February 2018
Sagar Sharma
Keke Chen
    FedML
ArXiv (abs)PDFHTML

Papers citing "Confidential Boosting with Random Linear Classifiers for Outsourced User-generated Data"

4 / 4 papers shown
GAN-based Domain Inference Attack
GAN-based Domain Inference AttackAAAI Conference on Artificial Intelligence (AAAI), 2022
Yuechun Gu
Keke Chen
151
12
0
22 Dec 2022
Confidential High-Performance Computing in the Public Cloud
Confidential High-Performance Computing in the Public CloudIEEE Internet Computing (IEEE Internet Comput.), 2022
Keke Chen
FedML
80
9
0
05 Dec 2022
Confined Gradient Descent: Privacy-preserving Optimization for Federated
  Learning
Confined Gradient Descent: Privacy-preserving Optimization for Federated Learning
Yanjun Zhang
Guangdong Bai
Xue Li
Surya Nepal
R. Ko
FedML
112
2
0
27 Apr 2021
Confidential Machine Learning on Untrusted Platforms: A Survey
Confidential Machine Learning on Untrusted Platforms: A Survey
Sagar Sharma
Keke Chen
FedML
224
16
0
15 Dec 2020
1
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