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. 2404.03216
  4. Cited By
Accurate Low-Degree Polynomial Approximation of Non-polynomial Operators
  for Fast Private Inference in Homomorphic Encryption
v1v2v3 (latest)

Accurate Low-Degree Polynomial Approximation of Non-polynomial Operators for Fast Private Inference in Homomorphic Encryption

Conference on Machine Learning and Systems (MLSys), 2024
4 April 2024
Jianming Tong
Jing Dang
Anupam Golder
Callie Hao
A. Raychowdhury
Tushar Krishna
ArXiv (abs)PDFHTMLGithub (17★)

Papers citing "Accurate Low-Degree Polynomial Approximation of Non-polynomial Operators for Fast Private Inference in Homomorphic Encryption"

4 / 4 papers shown
HHEML: Hybrid Homomorphic Encryption for Privacy-Preserving Machine Learning on Edge
HHEML: Hybrid Homomorphic Encryption for Privacy-Preserving Machine Learning on Edge
Yu Hin Chan
Hao Yang
Shiyu Shen
Xingyu Fan
Shengzhe Lyu
Patrick S. Y. Hung
Ray C. C. Cheung
77
0
0
23 Oct 2025
HEIR: A Universal Compiler for Homomorphic Encryption
HEIR: A Universal Compiler for Homomorphic Encryption
Asra Ali
Jaeho Choi
Bryant Gipson
Shruthi Gorantala
Jeremy Kun
Wouter Legiest
Lawrence Lim
Alexander Viand
Meron Zerihun Demissie
Hongren Zheng
59
4
0
14 Aug 2025
Fast and Accurate Homomorphic Softmax Evaluation
Fast and Accurate Homomorphic Softmax EvaluationConference on Computer and Communications Security (CCS), 2024
Wonhee Cho
G. Hanrot
Taeseong Kim
Minje Park
D. Stehlé
151
9
0
15 Oct 2024
Blind Evaluation Framework for Fully Homomorphic Encryption and
  Privacy-Preserving Machine Learning
Blind Evaluation Framework for Fully Homomorphic Encryption and Privacy-Preserving Machine Learning
Hunjae Lee
Corey Clark
184
0
0
19 Oct 2023
1