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zkDL: Efficient Zero-Knowledge Proofs of Deep Learning Training
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zkDL: Efficient Zero-Knowledge Proofs of Deep Learning Training

Hao Sun
Tonghe Bai
Jason Li
Hongyang R. Zhang
ArXiv (abs)PDFHTML

Papers citing "zkDL: Efficient Zero-Knowledge Proofs of Deep Learning Training"

12 / 12 papers shown
Title
Engineering Trustworthy Machine-Learning Operations with Zero-Knowledge Proofs
Engineering Trustworthy Machine-Learning Operations with Zero-Knowledge Proofs
Filippo Scaramuzza
Giovanni Quattrocchi
Damian A. Tamburri
30
0
0
26 May 2025
FairZK: A Scalable System to Prove Machine Learning Fairness in Zero-Knowledge
FairZK: A Scalable System to Prove Machine Learning Fairness in Zero-Knowledge
Tianyu Zhang
Shen Dong
O. Deniz Kose
Yanning Shen
Yanzhe Zhang
FaML
83
0
0
12 May 2025
A Framework for Cryptographic Verifiability of End-to-End AI Pipelines
A Framework for Cryptographic Verifiability of End-to-End AI Pipelines
Kar Balan
Robert Learney
Tim Wood
75
2
0
28 Mar 2025
A Survey of Zero-Knowledge Proof Based Verifiable Machine Learning
A Survey of Zero-Knowledge Proof Based Verifiable Machine Learning
Zhizhi Peng
Taotao Wang
Chonghe Zhao
Guofu Liao
Zibin Lin
Yixiao Liu
Bin Cao
Long Shi
Qing Yang
Shengli Zhang
108
5
0
25 Feb 2025
Towards Understanding and Enhancing Security of Proof-of-Training for DNN Model Ownership Verification
Towards Understanding and Enhancing Security of Proof-of-Training for DNN Model Ownership Verification
Yijia Chang
Hanrui Jiang
Chao Lin
Xinyi Huang
Jian Weng
AAML
143
0
0
06 Oct 2024
Model Agnostic Hybrid Sharding For Heterogeneous Distributed Inference
Model Agnostic Hybrid Sharding For Heterogeneous Distributed Inference
Claudio Angione
Yue Zhao
Harry Yang
Ahmad Farhan
Fielding Johnston
James Buban
Patrick Colangelo
90
1
0
29 Jul 2024
Laminator: Verifiable ML Property Cards using Hardware-assisted Attestations
Laminator: Verifiable ML Property Cards using Hardware-assisted Attestations
Vasisht Duddu
Oskari Jarvinen
Lachlan J. Gunn
Nirmal Asokan
153
1
0
25 Jun 2024
Trustless Audits without Revealing Data or Models
Trustless Audits without Revealing Data or Models
Suppakit Waiwitlikhit
Ion Stoica
Yi Sun
Tatsunori Hashimoto
Daniel Kang
MLAU
38
10
0
06 Apr 2024
Holding Secrets Accountable: Auditing Privacy-Preserving Machine Learning
Holding Secrets Accountable: Auditing Privacy-Preserving Machine Learning
Hidde Lycklama
Alexander Viand
Nicolas Küchler
Christian Knabenhans
Anwar Hithnawi
118
7
0
24 Feb 2024
Verifiable evaluations of machine learning models using zkSNARKs
Verifiable evaluations of machine learning models using zkSNARKs
Tobin South
Alexander Camuto
Shrey Jain
Shayla Nguyen
Robert Mahari
Christian Paquin
Jason Morton
Alex Pentland
MLAUALM
75
13
0
05 Feb 2024
DeepReShape: Redesigning Neural Networks for Efficient Private Inference
DeepReShape: Redesigning Neural Networks for Efficient Private Inference
N. Jha
Brandon Reagen
95
10
0
20 Apr 2023
Verifiable and Provably Secure Machine Unlearning
Verifiable and Provably Secure Machine Unlearning
Thorsten Eisenhofer
Doreen Riepel
Varun Chandrasekaran
Esha Ghosh
O. Ohrimenko
Nicolas Papernot
AAMLMU
102
27
0
17 Oct 2022

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