Correlating Cross-Iteration Noise for DP-SGD using Model Curvature | Paper Citation Record

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This paper cites write newline.

Correlating Cross-Iteration Noise for DP-SGD using Model Curvature write newline

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Correlating Cross-Iteration Noise for DP-SGD using Model Curvature @esa (Ref

Reference 2

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Correlating Cross-Iteration Noise for DP-SGD using Model Curvature Unresolved cited work

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Correlating Cross-Iteration Noise for DP-SGD using Model Curvature Unresolved cited work

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This paper cites Brendan McMahan, Ilya Mironov, Kunal Talwar, and Li Zhang.

Correlating Cross-Iteration Noise for DP-SGD using Model Curvature Brendan McMahan, Ilya Mironov, Kunal Talwar, and Li Zhang

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Correlating Cross-Iteration Noise for DP-SGD using Model Curvature Optuna: A next-generation hyperparameter optimization framework

Reference 6

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This paper cites Privacy amplification via random check-ins.

Correlating Cross-Iteration Noise for DP-SGD using Model Curvature Privacy amplification via random check-ins

Reference 7

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Observation 05d507c0-47d9-49cc-87b4-73dadd11e9f4 · outbound

This paper cites Automatic clipping: Differentially private deep learning made easier and stronger.

Correlating Cross-Iteration Noise for DP-SGD using Model Curvature Automatic clipping: Differentially private deep learning made easier and stronger

Reference 8

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Correlating Cross-Iteration Noise for DP-SGD using Model Curvature Differentially private optimization on large model at small cost

Reference 9

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This paper cites A simple framework for contrastive learning of visual representations.

Correlating Cross-Iteration Noise for DP-SGD using Model Curvature A simple framework for contrastive learning of visual representations

Reference 10

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This paper cites Choquette-Choo, Arun Ganesh, Ryan McKenna, Hugh Brendan McMahan, J Keith Rush, Abhradeep Guha Thakurta, and Zheng Xu.

Correlating Cross-Iteration Noise for DP-SGD using Model Curvature Choquette-Choo, Arun Ganesh, Ryan McKenna, Hugh Brendan McMahan, J Keith Rush, Abhradeep Guha Thakurta, and Zheng Xu

Reference 11

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This paper cites Choquette-Choo, H.

Correlating Cross-Iteration Noise for DP-SGD using Model Curvature Choquette-Choo, H

Reference 12

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Observation 2dfbea16-0d05-4d4e-8c08-23985a47b764 · outbound

This paper cites Mind the Privacy Unit! User-Level Differential Privacy for Language Model Fine-Tuning.

Correlating Cross-Iteration Noise for DP-SGD using Model Curvature Mind the Privacy Unit! User-Level Differential Privacy for Language Model Fine-Tuning

Reference 13

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Observation 9863961d-59f2-4548-a21a-a06a5c458366 · outbound

This paper cites Scalable DP - SGD : Shuffling vs.

Correlating Cross-Iteration Noise for DP-SGD using Model Curvature Scalable DP - SGD : Shuffling vs

Reference 14

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This paper cites Unlocking High-Accuracy Differentially Private Image Classification through Scale.

Correlating Cross-Iteration Noise for DP-SGD using Model Curvature Unlocking High-Accuracy Differentially Private Image Classification through Scale

Reference 15

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Correlating Cross-Iteration Noise for DP-SGD using Model Curvature Brendan McMahan, John Rush, Adam Smith, and Abhradeep Guha Thakurta

Reference 16

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This paper cites An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale.

Correlating Cross-Iteration Noise for DP-SGD using Model Curvature An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale

Reference 17

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This paper cites Brendan McMahan, Krishna Pillutla, Thomas Steinke, and Abhradeep Thakurta.

Correlating Cross-Iteration Noise for DP-SGD using Model Curvature Brendan McMahan, Krishna Pillutla, Thomas Steinke, and Abhradeep Thakurta

Reference 18

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Observation 73eb1380-4d53-476a-aa6b-cd2b4ce78758 · outbound

This paper cites Our data, ourselves: privacy via distributed noise generation.

Correlating Cross-Iteration Noise for DP-SGD using Model Curvature Our data, ourselves: privacy via distributed noise generation

Reference 19

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Observation f130df97-dcc7-4837-8b3d-3d0f8dc2536c · outbound

This paper cites Calibrating noise to sensitivity in private data analysis.

Correlating Cross-Iteration Noise for DP-SGD using Model Curvature Calibrating noise to sensitivity in private data analysis

Reference 20

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Observation a1d21012-e0b3-4ac3-8d0e-417dd36c7fdd · outbound

This paper cites Privacy amplification by random allocation, 2025.

Correlating Cross-Iteration Noise for DP-SGD using Model Curvature Privacy amplification by random allocation, 2025

Reference 21

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This paper cites Tighter Privacy Analysis for Truncated Poisson Sampling.

Correlating Cross-Iteration Noise for DP-SGD using Model Curvature Tighter Privacy Analysis for Truncated Poisson Sampling

Reference 22

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This paper cites Faster differentially private convex optimization via second-order methods.

Correlating Cross-Iteration Noise for DP-SGD using Model Curvature Faster differentially private convex optimization via second-order methods

Reference 23

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Correlating Cross-Iteration Noise for DP-SGD using Model Curvature On Design Principles for Private Adaptive Optimizers

Reference 24

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This paper cites An investigation into neural net optimization via hessian eigenvalue density.

Correlating Cross-Iteration Noise for DP-SGD using Model Curvature An investigation into neural net optimization via hessian eigenvalue density

Reference 25

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Correlating Cross-Iteration Noise for DP-SGD using Model Curvature Understanding the difficulty of training deep feedforward neural networks

Reference 26

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This paper cites G rammarly: F ree A I W riting A ssistance --- grammarly.com.

Correlating Cross-Iteration Noise for DP-SGD using Model Curvature G rammarly: F ree A I W riting A ssistance --- grammarly.com

Reference 27

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Correlating Cross-Iteration Noise for DP-SGD using Model Curvature pfl-research: simulation framework for accelerating research in Private Federated Learning

Reference 28

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This paper cites Choosing public datasets for private machine learning via gradient subspace distance.

Correlating Cross-Iteration Noise for DP-SGD using Model Curvature Choosing public datasets for private machine learning via gradient subspace distance

Reference 29

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Correlating Cross-Iteration Noise for DP-SGD using Model Curvature Gradient Descent Happens in a Tiny Subspace

Reference 30

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This paper cites Delving Deep into Rectifiers: Surpassing Human-Level Performance on ImageNet Classification.

Correlating Cross-Iteration Noise for DP-SGD using Model Curvature Delving Deep into Rectifiers: Surpassing Human-Level Performance on ImageNet Classification

Reference 31

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Correlating Cross-Iteration Noise for DP-SGD using Model Curvature Deep residual learning for image recognition

Reference 32

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Correlating Cross-Iteration Noise for DP-SGD using Model Curvature Lo RA : Low-rank adaptation of large language models

Reference 33

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Correlating Cross-Iteration Noise for DP-SGD using Model Curvature Practical and private (deep) learning without sampling or shuffling

Reference 34

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Correlating Cross-Iteration Noise for DP-SGD using Model Curvature Back to square roots: An optimal bound on the matrix factorization error for multi-epoch differentially private sgd

Reference 35

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Correlating Cross-Iteration Noise for DP-SGD using Model Curvature Kingma and Jimmy Ba

Reference 36

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Correlating Cross-Iteration Noise for DP-SGD using Model Curvature Gradient descent with linearly correlated noise: theory and applications to differential privacy

Reference 37

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Correlating Cross-Iteration Noise for DP-SGD using Model Curvature Learning multiple layers of features from tiny images

Reference 38

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Correlating Cross-Iteration Noise for DP-SGD using Model Curvature Toward Training at ImageNet Scale with Differential Privacy

Reference 39

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Correlating Cross-Iteration Noise for DP-SGD using Model Curvature An iteration method for the solution of the eigenvalue problem of linear differential and integral operators

Reference 40

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Correlating Cross-Iteration Noise for DP-SGD using Model Curvature Tiny imagenet visual recognition challenge

Reference 41

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Correlating Cross-Iteration Noise for DP-SGD using Model Curvature Concentrated Differentially Private Gradient Descent with Adaptive per-Iteration Privacy Budget

Reference 42

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Correlating Cross-Iteration Noise for DP-SGD using Model Curvature Scaling up differentially private deep learning with fast per-example gradient clipping

Reference 43

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Correlating Cross-Iteration Noise for DP-SGD using Model Curvature Reddi, Hugh Brendan McMahan, and Virginia Smith

Reference 44

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Correlating Cross-Iteration Noise for DP-SGD using Model Curvature Large language models can be strong differentially private learners

Reference 45

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Correlating Cross-Iteration Noise for DP-SGD using Model Curvature Large language models can be strong differentially private learners

Reference 46

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Correlating Cross-Iteration Noise for DP-SGD using Model Curvature An Inversion Theorem for Buffered Linear Toeplitz (BLT) Matrices and Applications to Streaming Differential Privacy

Reference 47

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Correlating Cross-Iteration Noise for DP-SGD using Model Curvature Unresolved cited work

Reference 48

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Correlating Cross-Iteration Noise for DP-SGD using Model Curvature Updating quasi-newton matrices with limited storage

Reference 49

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Correlating Cross-Iteration Noise for DP-SGD using Model Curvature The Full Spectrum of Deepnet Hessians at Scale: Dynamics with SGD Training and Sample Size

Reference 50

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Correlating Cross-Iteration Noise for DP-SGD using Model Curvature PyTorch: an imperative style, high-performance deep learning library

Reference 51

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Correlating Cross-Iteration Noise for DP-SGD using Model Curvature Correlated Noise Mechanisms for Differentially Private Learning

Reference 52

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Correlating Cross-Iteration Noise for DP-SGD using Model Curvature Eigenvalues of the Hessian in Deep Learning: Singularity and Beyond

Reference 53

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Correlating Cross-Iteration Noise for DP-SGD using Model Curvature Very Deep Convolutional Networks for Large-Scale Image Recognition

Reference 54

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Correlating Cross-Iteration Noise for DP-SGD using Model Curvature Deep image prior

Reference 55

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Correlating Cross-Iteration Noise for DP-SGD using Model Curvature Chestx-ray8: Hospital-scale chest x-ray database and benchmarks on weakly-supervised classification and localization of common thorax diseases

Reference 56

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This paper cites Opacus: User-Friendly Differential Privacy Library in PyTorch.

Correlating Cross-Iteration Noise for DP-SGD using Model Curvature Opacus: User-Friendly Differential Privacy Library in PyTorch

Reference 57

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This paper cites Do not let privacy overbill utility: Gradient embedding perturbation for private learning.

Correlating Cross-Iteration Noise for DP-SGD using Model Curvature Do not let privacy overbill utility: Gradient embedding perturbation for private learning

Reference 58

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Correlating Cross-Iteration Noise for DP-SGD using Model Curvature Differentially private fine-tuning of language models

Reference 59

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This paper cites Bypassing the ambient dimension: Private \ sgd \ with gradient subspace identification.

Correlating Cross-Iteration Noise for DP-SGD using Model Curvature Bypassing the ambient dimension: Private \ sgd \ with gradient subspace identification

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