Paper Citation Record · LEDGER

NysAct: A Scalable Preconditioned Gradient Descent using Nystrom Approximation

As of 9 August 2026, this Paper Citation Record lists 41 of 41 outbound references and 0 inbound Pith citation observations for arXiv:2506.08360.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
2506.08360 v1

Coverage vector

measured 41 of 41 reference resolution

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Source: paper_references, paper_reference_links, observed 2026-08-07T05:21:43.961303Z

measured 41 of 41 standing notices

One-hop event checks from named stored sources.

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measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

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measured 0 of 1 external citation measurements

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Source: cited_works

Reference resolution

41 of 41 outbound references displayed

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External citation measurements

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Outbound references

Observation 894cbacf-f12d-4614-bd66-13dc020069d9 · outbound

This paper cites Efficient full-matrix adaptive regularization.

NysAct: A Scalable Preconditioned Gradient Descent using Nystrom Approximation Efficient full-matrix adaptive regularization

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:21:44.544773Z

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Observation 503dd169-4cbe-4a26-a8e9-85e4355dc15a · outbound

This paper cites Gradient descent on neurons and its link to approximate second-order optimization.

NysAct: A Scalable Preconditioned Gradient Descent using Nystrom Approximation Gradient descent on neurons and its link to approximate second-order optimization

Reference 2

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NysAct: A Scalable Preconditioned Gradient Descent using Nystrom Approximation Unresolved cited work

Reference 3

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NysAct: A Scalable Preconditioned Gradient Descent using Nystrom Approximation Unresolved cited work

Reference 4

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Observation cfa1fd1b-94ad-47ff-8b33-dade0fd73526 · outbound

This paper cites Imagenet: A large-scale hierarchical image database.

NysAct: A Scalable Preconditioned Gradient Descent using Nystrom Approximation Imagenet: A large-scale hierarchical image database

Reference 5

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Observation c2cd5995-36dd-4db4-8897-3b8d7794bb51 · outbound

This paper cites Fletcher.

NysAct: A Scalable Preconditioned Gradient Descent using Nystrom Approximation Fletcher

Reference 6

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Observation 7dd34c60-11b4-45ed-9d28-290d8faf9dfa · outbound

This paper cites Sketchysgd: reliable stochastic optimization via randomized curvature estimates.

NysAct: A Scalable Preconditioned Gradient Descent using Nystrom Approximation Sketchysgd: reliable stochastic optimization via randomized curvature estimates

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:21:44.461977Z

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Observation 5b2f41fe-959f-43e4-8265-14bef42c7301 · outbound

This paper cites Tropp, and Madeleine Udell.

NysAct: A Scalable Preconditioned Gradient Descent using Nystrom Approximation Tropp, and Madeleine Udell

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:21:44.446090Z

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Observation f122456a-c5fd-487f-a570-5702d7acbcdd · outbound

This paper cites M-FAC: Efficient matrix-free approximations of second-order information.

NysAct: A Scalable Preconditioned Gradient Descent using Nystrom Approximation M-FAC: Efficient matrix-free approximations of second-order information

Reference 9

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Observation 4d62d7fd-11bd-4cde-8fa8-e0ca96f860bb · outbound

This paper cites A family of variable-metric methods derived by variational means.Mathematics of Computation, 1970.

NysAct: A Scalable Preconditioned Gradient Descent using Nystrom Approximation A family of variable-metric methods derived by variational means.Mathematics of Computation, 1970

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:21:44.416976Z

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Observation 668e86af-09c0-4d69-bee2-5a2b63e5b655 · outbound

This paper cites Practical quasi-newton methods for training deep neural networks.

NysAct: A Scalable Preconditioned Gradient Descent using Nystrom Approximation Practical quasi-newton methods for training deep neural networks

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:21:44.402382Z

Source-reported events for the cited work

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Observation 3be394f9-344e-4f0f-bef7-a867c634bfdb · outbound

This paper cites Girshick, Pieter Noordhuis, Lukasz Wesolowski, Aapo Kyrola, Andrew Tulloch, Yangqing Jia, and Kaiming He.

NysAct: A Scalable Preconditioned Gradient Descent using Nystrom Approximation Girshick, Pieter Noordhuis, Lukasz Wesolowski, Aapo Kyrola, Andrew Tulloch, Yangqing Jia, and Kaiming He

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:21:44.387964Z

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Observation 7ac955a6-59a2-43e6-ba46-aecb3de89c5f · outbound

This paper cites Shampoo: Preconditioned stochastic tensor optimization.

NysAct: A Scalable Preconditioned Gradient Descent using Nystrom Approximation Shampoo: Preconditioned stochastic tensor optimization

Reference 13

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Observation 969d0e74-c4b3-4d6f-9f58-fee0189b94c3 · outbound

This paper cites Deep residual learning for image recognition.

NysAct: A Scalable Preconditioned Gradient Descent using Nystrom Approximation Deep residual learning for image recognition

Reference 14

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Observation 640a7efc-5f90-42c0-b26f-978e61eaf16b · outbound

This paper cites Augment your batch: better training with larger batches.

NysAct: A Scalable Preconditioned Gradient Descent using Nystrom Approximation Augment your batch: better training with larger batches

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:21:44.354294Z

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Observation 0b207aae-d426-4425-9cc5-08f9af165e66 · outbound

This paper cites Train longer, generalize better: closing the generalization gap in large batch training of neural networks.

NysAct: A Scalable Preconditioned Gradient Descent using Nystrom Approximation Train longer, generalize better: closing the generalization gap in large batch training of neural networks

Reference 16

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Observation ff858c24-0277-4f07-ac48-c132bd715248 · outbound

This paper cites Weinberger.

NysAct: A Scalable Preconditioned Gradient Descent using Nystrom Approximation Weinberger

Reference 17

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Observation fc2bfd1c-d938-499b-b15b-e1ce46e297bf · outbound

This paper cites Weinberger.

NysAct: A Scalable Preconditioned Gradient Descent using Nystrom Approximation Weinberger

Reference 18

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Observation 3343c7e4-8acb-408b-b8f4-29781ac582e8 · outbound

This paper cites Kingma and Jimmy Ba.

NysAct: A Scalable Preconditioned Gradient Descent using Nystrom Approximation Kingma and Jimmy Ba

Reference 19

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Observation 12996438-b785-4774-af47-9f5f3e2850ff · outbound

This paper cites Learning multiple layers of features from tiny images.

NysAct: A Scalable Preconditioned Gradient Descent using Nystrom Approximation Learning multiple layers of features from tiny images

Reference 20

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Observation a143749b-51c4-4829-83a6-e05adfd361e2 · outbound

This paper cites Lecun, L.

NysAct: A Scalable Preconditioned Gradient Descent using Nystrom Approximation Lecun, L

Reference 21

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Observation a2acc989-28f9-4026-b611-8f0b0ce5f2d5 · outbound

This paper cites Sophia: A scalable stochastic second-order optimizer for language model pre-training.

NysAct: A Scalable Preconditioned Gradient Descent using Nystrom Approximation Sophia: A scalable stochastic second-order optimizer for language model pre-training

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:21:44.265838Z

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Observation 65fefbdb-e643-4921-b935-5fbb15b83c06 · outbound

This paper cites Sgdr: Stochastic gradient descent with warm restarts.

NysAct: A Scalable Preconditioned Gradient Descent using Nystrom Approximation Sgdr: Stochastic gradient descent with warm restarts

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:21:44.251522Z

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No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 2d64b463-123b-41d7-8f66-4e19b4cfb1e3 · outbound

This paper cites Decoupled weight decay regularization.

NysAct: A Scalable Preconditioned Gradient Descent using Nystrom Approximation Decoupled weight decay regularization

Reference 24

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Observation 270ecbdb-7fc1-46ba-aca9-b866c95678a5 · outbound

This paper cites Optimizing neural networks with kronecker-factored approximate curvature.

NysAct: A Scalable Preconditioned Gradient Descent using Nystrom Approximation Optimizing neural networks with kronecker-factored approximate curvature

Reference 25

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Observation 0dee1a5a-6d05-479a-a22b-7abe4eba278d · outbound

This paper cites Müller and Frank Hutter.

NysAct: A Scalable Preconditioned Gradient Descent using Nystrom Approximation Müller and Frank Hutter

Reference 26

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Observation f902bb00-4b53-433c-beb6-b769e3f39c69 · outbound

This paper cites Pytorch: An imperative style, high-performance deep learning library.

NysAct: A Scalable Preconditioned Gradient Descent using Nystrom Approximation Pytorch: An imperative style, high-performance deep learning library

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:21:44.203425Z

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Observation 6c741606-3c12-417d-8f2a-10f01c926df0 · outbound

This paper cites Sublinear time approximation of text similarity matrices.

NysAct: A Scalable Preconditioned Gradient Descent using Nystrom Approximation Sublinear time approximation of text similarity matrices

Reference 28

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No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation d2798688-a2df-4571-b600-6f1417088129 · outbound

This paper cites A stochastic approximation method.

NysAct: A Scalable Preconditioned Gradient Descent using Nystrom Approximation A stochastic approximation method

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:21:44.173580Z

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Observation 99dfc4d4-0a85-4cad-929f-507c6f94d191 · outbound

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NysAct: A Scalable Preconditioned Gradient Descent using Nystrom Approximation Unresolved cited work

Reference 30

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Observation df231b7a-0fb6-4a59-ae0f-650dc8e78a6f · outbound

This paper cites Rethinking the inception architecture for computer vision.

NysAct: A Scalable Preconditioned Gradient Descent using Nystrom Approximation Rethinking the inception architecture for computer vision

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:21:44.145671Z

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This paper cites Skfac: Training neural networks with faster kronecker-factored approximate curvature.

NysAct: A Scalable Preconditioned Gradient Descent using Nystrom Approximation Skfac: Training neural networks with faster kronecker-factored approximate curvature

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:21:44.131566Z

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Observation f26a976c-b8d8-4fe8-bca3-8244c150dd17 · outbound

This paper cites Training data-efficient image transformers & distillation through attention.

NysAct: A Scalable Preconditioned Gradient Descent using Nystrom Approximation Training data-efficient image transformers & distillation through attention

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:21:44.117185Z

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Observation fe7b1a5a-e061-4569-9c67-ae728ea2b5f1 · outbound

This paper cites Better SGD using second-order momentum.

NysAct: A Scalable Preconditioned Gradient Descent using Nystrom Approximation Better SGD using second-order momentum

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:21:44.101439Z

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Observation 9cc146dd-74d2-4665-a2a0-01eac1b73ca5 · outbound

This paper cites Tropp, Alp Yurtsever, Madeleine Udell, and V olkan Cevher.

NysAct: A Scalable Preconditioned Gradient Descent using Nystrom Approximation Tropp, Alp Yurtsever, Madeleine Udell, and V olkan Cevher

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:21:44.086402Z

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Observation f14b78de-52a6-4ebf-9d0c-b4dc3ffff3e7 · outbound

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NysAct: A Scalable Preconditioned Gradient Descent using Nystrom Approximation Unresolved cited work

Reference 36

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Observation 809a5bca-1f83-4580-98a3-c8fe4eda8196 · outbound

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NysAct: A Scalable Preconditioned Gradient Descent using Nystrom Approximation Unresolved cited work

Reference 37

Resolution: unresolved; raw_fallback, observed 2026-08-07T05:21:44.056168Z

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Observation 1ae7991a-f570-4c81-b07a-5859e0a914a4 · outbound

This paper cites Cutmix: Regularization strategy to train strong classifiers with localizable features.

NysAct: A Scalable Preconditioned Gradient Descent using Nystrom Approximation Cutmix: Regularization strategy to train strong classifiers with localizable features

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:21:44.041577Z

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Observation d8024c27-cedd-4df6-9153-2146a12c6bcc · outbound

This paper cites Dauphin, and David Lopez-Paz.

NysAct: A Scalable Preconditioned Gradient Descent using Nystrom Approximation Dauphin, and David Lopez-Paz

Reference 39

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Observation 0186fdc4-0fc5-4727-b45c-0bbece7eb254 · outbound

This paper cites Eva: Practical second-order optimization with kronecker-vectorized approximation.

NysAct: A Scalable Preconditioned Gradient Descent using Nystrom Approximation Eva: Practical second-order optimization with kronecker-vectorized approximation

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:21:44.014992Z

Source-reported events for the cited work

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Observation 2ec94dc4-bb78-40cd-89c9-2a0745b1adbe · outbound

This paper cites Random erasing data augmentation.

NysAct: A Scalable Preconditioned Gradient Descent using Nystrom Approximation Random erasing data augmentation

Reference 41

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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