Paper Citation Record · LEDGER

Regularizing CNN Transfer Learning with Randomised Regression

As of 16 August 2026, this Paper Citation Record lists 51 of 51 outbound references and 0 inbound Pith citation observations for arXiv:1908.05997.

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

pith.paper-citation-record.v1
1908.05997 v2

Coverage vector

measured 51 of 51 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-14T13:03:08.885556Z

measured 51 of 51 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-16T06:30:59.297886+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: cited_works

Reference resolution

51 of 51 outbound references displayed

verified exact0
verified fuzzy37
unresolved14
parse uncertain0
malformed identifier0
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 43e196fe-eacb-4c08-bef7-261d97ff3393 · outbound

This paper cites Factors of transferability for a generic convnet representation.

Regularizing CNN Transfer Learning with Randomised Regression Factors of transferability for a generic convnet representation

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T13:03:09.385552Z

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Observation c68f1a35-da1a-49d2-ad96-6472e300cc77 · outbound

This paper cites Gradnorm: Gradient normalization for adaptive loss balancing in deep multitask networks.

Regularizing CNN Transfer Learning with Randomised Regression Gradnorm: Gradient normalization for adaptive loss balancing in deep multitask networks

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T13:03:09.371271Z

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Observation ce86d0c9-f157-495d-82cf-1841b724da29 · outbound

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

Regularizing CNN Transfer Learning with Randomised Regression Imagenet: A large-scale hierarchical image database

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T13:03:09.360522Z

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Observation 2cdc19ba-e7d5-4da0-beef-94d4dd4d8257 · outbound

This paper cites Decaf: A deep convolutional activation feature for generic visual recognition.

Regularizing CNN Transfer Learning with Randomised Regression Decaf: A deep convolutional activation feature for generic visual recognition

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T13:03:09.350047Z

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Observation 3aaafd2d-2aa9-43d4-8200-da10ff7035dc · outbound

This paper cites Pairwise confusion for fine-grained visual classification.

Regularizing CNN Transfer Learning with Randomised Regression Pairwise confusion for fine-grained visual classification

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T13:03:09.339285Z

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Observation 189638ab-7223-48a5-b934-eb35dbaaab8b · outbound

This paper cites Borrowing treasures from the wealthy: Deep transfer learning through selective joint fine-tuning.

Regularizing CNN Transfer Learning with Randomised Regression Borrowing treasures from the wealthy: Deep transfer learning through selective joint fine-tuning

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T13:03:09.329622Z

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Observation 36bca4bc-504e-4e17-baa8-1c6d3d809114 · outbound

This paper cites Accurate, Large Minibatch SGD: Training ImageNet in 1 Hour.

Regularizing CNN Transfer Learning with Randomised Regression Accurate, Large Minibatch SGD: Training ImageNet in 1 Hour

Reference 7

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Observation 6c3b8e6d-4022-4850-9ba8-97f25b22e53d · outbound

This paper cites Caltech-256 object category dataset.

Regularizing CNN Transfer Learning with Randomised Regression Caltech-256 object category dataset

Reference 8

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Observation 0f7361ff-927d-40d3-8db7-2bf6b4f32320 · outbound

This paper cites Weinberger.

Regularizing CNN Transfer Learning with Randomised Regression Weinberger

Reference 9

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Observation 8f11a426-d901-41b5-994f-f3ad65eba95d · outbound

This paper cites Low-shot visual recognition by shrinking and hallucinating features.

Regularizing CNN Transfer Learning with Randomised Regression Low-shot visual recognition by shrinking and hallucinating features

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T13:03:09.302666Z

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Observation 305f1e9d-5bf3-416f-9aa8-f74149ae84d4 · outbound

This paper cites Deep residual learning for image recognition.

Regularizing CNN Transfer Learning with Randomised Regression Deep residual learning for image recognition

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T13:03:09.292316Z

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Observation e58fd1c5-b26d-4430-a01b-e44081d470bd · outbound

This paper cites Weinberger.

Regularizing CNN Transfer Learning with Randomised Regression Weinberger

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T13:03:09.282962Z

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Observation b9345fab-ff1b-404a-8b50-bca64065c7fd · outbound

This paper cites Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift.

Regularizing CNN Transfer Learning with Randomised Regression Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift

Reference 13

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Observation 31d168f8-5689-4179-9281-912b16a2064b · outbound

This paper cites Three Factors Influencing Minima in SGD.

Regularizing CNN Transfer Learning with Randomised Regression Three Factors Influencing Minima in SGD

Reference 14

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Observation 89386a8e-e1bf-4ef7-ac89-7236fdf0df64 · outbound

This paper cites One millisecond face alignment with an ensemble of regression trees.

Regularizing CNN Transfer Learning with Randomised Regression One millisecond face alignment with an ensemble of regression trees

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T13:03:09.273495Z

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Observation 11039612-f48b-4c76-954c-a1baa10bccf4 · outbound

This paper cites Pose N et: A convolutional network for real-time 6-dof camera relocalization.

Regularizing CNN Transfer Learning with Randomised Regression Pose N et: A convolutional network for real-time 6-dof camera relocalization

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T13:03:09.263463Z

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Observation 4211a0fb-4e38-4c98-831e-c8cc95df793d · outbound

This paper cites On large-batch training for deep learning: Generalization gap and sharp minima.

Regularizing CNN Transfer Learning with Randomised Regression On large-batch training for deep learning: Generalization gap and sharp minima

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T13:03:09.254027Z

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Observation 708b7f50-d77b-4faf-bc7d-17c18b899c91 · outbound

This paper cites an unresolved cited work.

Regularizing CNN Transfer Learning with Randomised Regression Unresolved cited work

Reference 18

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Observation 05555634-4876-43e8-a732-76ec45530ab6 · outbound

This paper cites Feature contraction: New convnet regularization in image classification.

Regularizing CNN Transfer Learning with Randomised Regression Feature contraction: New convnet regularization in image classification

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T13:03:09.234894Z

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Observation 29f9d903-f5f7-4ea3-92e0-8e9c1584e2b7 · outbound

This paper cites Explicit inductive bias for transfer learning with convolutional networks.

Regularizing CNN Transfer Learning with Randomised Regression Explicit inductive bias for transfer learning with convolutional networks

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T13:03:09.225657Z

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Observation a8d70a07-8698-41e8-80e9-107140dbce9d · outbound

This paper cites Learning without forgetting.

Regularizing CNN Transfer Learning with Randomised Regression Learning without forgetting

Reference 21

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Observation ac5db786-9611-4d93-99c3-ce54c3e5927b · outbound

This paper cites Lawrence Zitnick.

Regularizing CNN Transfer Learning with Randomised Regression Lawrence Zitnick

Reference 22

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Observation 89083ccb-a76c-480b-ba43-c8c63a3c50e0 · outbound

This paper cites Deep learning face attributes in the wild.

Regularizing CNN Transfer Learning with Randomised Regression Deep learning face attributes in the wild

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T13:03:09.196635Z

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Observation 0bbd3d43-4c08-46a3-a0f3-5e1368a07857 · outbound

This paper cites Learning transferable features with deep adaptation networks.

Regularizing CNN Transfer Learning with Randomised Regression Learning transferable features with deep adaptation networks

Reference 24

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This paper cites Toward principled regularization of deep networks—from weight decay to feature contraction.

Regularizing CNN Transfer Learning with Randomised Regression Toward principled regularization of deep networks—from weight decay to feature contraction

Reference 25

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Observation 2957d79d-98bc-4433-b8ef-31c20e70506d · outbound

This paper cites Curriculum dropout.

Regularizing CNN Transfer Learning with Randomised Regression Curriculum dropout

Reference 26

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Observation 8b1df7c5-9116-4e02-bb6e-0f03302c4ea6 · outbound

This paper cites Automated flower classification over a large number of classes.

Regularizing CNN Transfer Learning with Randomised Regression Automated flower classification over a large number of classes

Reference 27

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Observation 68c832cc-ffe7-4ad7-8bb8-23576e560fc8 · outbound

This paper cites Learning and transferring mid-level image representations using convolutional neural networks.

Regularizing CNN Transfer Learning with Randomised Regression Learning and transferring mid-level image representations using convolutional neural networks

Reference 28

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Observation 79aa299b-b9a1-4957-b10c-10b35dcd8288 · outbound

This paper cites Automatic differentiation in pytorch.

Regularizing CNN Transfer Learning with Randomised Regression Automatic differentiation in pytorch

Reference 29

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This paper cites Recognizing indoor scenes.

Regularizing CNN Transfer Learning with Randomised Regression Recognizing indoor scenes

Reference 30

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Observation 87021d50-262f-4635-802b-086093510322 · outbound

This paper cites Very Deep Convolutional Networks for Large-Scale Image Recognition.

Regularizing CNN Transfer Learning with Randomised Regression Very Deep Convolutional Networks for Large-Scale Image Recognition

Reference 31

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This paper cites Dropout: A simple way to prevent neural networks from overfitting.

Regularizing CNN Transfer Learning with Randomised Regression Dropout: A simple way to prevent neural networks from overfitting

Reference 32

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Observation 0761e2ba-6e1b-41b8-86a4-d2dda160de87 · outbound

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Regularizing CNN Transfer Learning with Randomised Regression Going deeper with convolutions

Reference 33

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Observation 1a8e9f92-9b72-4307-913b-1701a6444615 · outbound

This paper cites Simultaneous deep transfer across domains and tasks.

Regularizing CNN Transfer Learning with Randomised Regression Simultaneous deep transfer across domains and tasks

Reference 34

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Observation d6a482d8-1f1e-49e4-8d83-d1b41964ed03 · outbound

This paper cites The Caltech-UCSD Birds-200-2011 Dataset.

Regularizing CNN Transfer Learning with Randomised Regression The Caltech-UCSD Birds-200-2011 Dataset

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T13:03:09.101598Z

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Observation 8287d9ee-4944-4ed6-91fe-2b4ffc0f0fec · outbound

This paper cites Disturblabel: Regularizing cnn on the loss layer.

Regularizing CNN Transfer Learning with Randomised Regression Disturblabel: Regularizing cnn on the loss layer

Reference 36

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Observation 2aff1c9b-4795-42b0-8dc7-8a0692958069 · outbound

This paper cites Human action recognition by learning bases of action attributes and parts.

Regularizing CNN Transfer Learning with Randomised Regression Human action recognition by learning bases of action attributes and parts

Reference 37

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Observation 859b9955-538f-4006-8e9a-89352e62e030 · outbound

This paper cites Learning Face Representation from Scratch.

Regularizing CNN Transfer Learning with Randomised Regression Learning Face Representation from Scratch

Reference 38

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Observation 1315fe39-9d8d-46d5-8bee-7ab70183bfb8 · outbound

This paper cites How transferable are features in deep neural networks? In Advances in Neural Information Processing Systems 27.

Regularizing CNN Transfer Learning with Randomised Regression How transferable are features in deep neural networks? In Advances in Neural Information Processing Systems 27

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T13:03:09.070457Z

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Observation a37eb8c7-d036-42a1-a7a6-ff41ad3be77a · outbound

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Regularizing CNN Transfer Learning with Randomised Regression Zeiler and Rob Fergus

Reference 40

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Observation 6282828f-52fa-4e2a-8f56-ebcd29a4912f · outbound

This paper cites A modulation module for multi-task learning with applications in image retrieval.

Regularizing CNN Transfer Learning with Randomised Regression A modulation module for multi-task learning with applications in image retrieval

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T13:03:09.049379Z

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Observation e80e1eb2-fcbf-4e1a-b255-3c4e559977dd · outbound

This paper cites The anisotropic noise in stochastic gradient descent: Its behavior of escaping from sharp minima and regularization effects.

Regularizing CNN Transfer Learning with Randomised Regression The anisotropic noise in stochastic gradient descent: Its behavior of escaping from sharp minima and regularization effects

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T13:03:09.038966Z

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Observation b8e78065-3214-47c6-b120-2e69f8e9727e · outbound

This paper cites write newline.

Regularizing CNN Transfer Learning with Randomised Regression write newline

Reference 43

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Regularizing CNN Transfer Learning with Randomised Regression Unresolved cited work

Reference 44

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Observation 5640ad82-9f6f-47ad-8454-95573f000418 · outbound

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Regularizing CNN Transfer Learning with Randomised Regression Dubey, O

Reference 45

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T13:03:09.011753Z

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Observation b6aa6f15-d157-4e34-bd3c-ca35fff78cda · outbound

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Regularizing CNN Transfer Learning with Randomised Regression Ge and Y

Reference 46

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T13:03:09.002176Z

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Observation b0a56b89-f1f6-4cb7-b650-81a3421f95eb · outbound

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Regularizing CNN Transfer Learning with Randomised Regression Krizhevsky

Reference 47

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Observation 43f747b4-4efa-4b69-9458-75c649111c40 · outbound

This paper cites LeCun and C.

Regularizing CNN Transfer Learning with Randomised Regression LeCun and C

Reference 48

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T13:03:08.987565Z

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Observation f21d3c84-ef27-409d-8511-302618a88b54 · outbound

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Regularizing CNN Transfer Learning with Randomised Regression Unresolved cited work

Reference 49

Resolution: unresolved; raw_fallback, observed 2026-08-14T13:03:08.977328Z

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Observation 2ed6cb93-de2a-4c8b-966b-0743113e06ea · outbound

This paper cites Li and D.

Regularizing CNN Transfer Learning with Randomised Regression Li and D

Reference 50

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T13:03:08.967402Z

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Observation 2e0e8cbe-2965-40f3-a15f-69e2f7182308 · outbound

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Regularizing CNN Transfer Learning with Randomised Regression Unresolved cited work

Reference 51

Resolution: unresolved; raw_fallback, observed 2026-08-14T13:03:08.957612Z

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Pith citing papers

No inbound Pith citation observations are available.