Paper Citation Record · LEDGER

Local Differential Privacy for Deep Learning

As of 21 August 2026, this Paper Citation Record lists 51 of 51 outbound references and 0 inbound Pith citation observations for arXiv:1908.02997.

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

pith.paper-citation-record.v1
1908.02997 v3

Coverage vector

measured 51 of 51 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-14T14:36:35.797559Z

measured 51 of 51 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-21T06:32:19.484+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 exact2
verified fuzzy35
unresolved14
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation e2ee45af-36be-46a8-812e-ff0362d10639 · outbound

This paper cites Deep learning with differential privacy,.

Local Differential Privacy for Deep Learning Deep learning with differential privacy,

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-14T14:36:35.541553Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b0744473-4661-4041-b006-d961dcfa6ef6 · outbound

This paper cites Membership inference attacks against machine learning models,.

Local Differential Privacy for Deep Learning Membership inference attacks against machine learning models,

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T14:36:36.779642Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation ad15fb4e-fdb7-4d2e-824d-93b6d1b19e83 · outbound

This paper cites Tensorﬂow: a system for large- scale machine learning.

Local Differential Privacy for Deep Learning Tensorﬂow: a system for large- scale machine learning

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-14T14:36:35.553392Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 662584df-7bde-4d6e-8042-25f0f93ef6b9 · outbound

This paper cites Distributed graphlab: a framework for machine learning and data mining in the cloud,.

Local Differential Privacy for Deep Learning Distributed graphlab: a framework for machine learning and data mining in the cloud,

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-14T14:36:35.559821Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8472b1fe-daff-4b03-8f95-dae7eefd3b1b · outbound

This paper cites Machine learning models that remember too much,.

Local Differential Privacy for Deep Learning Machine learning models that remember too much,

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T14:36:36.618144Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 497b5006-aeb5-46d2-a75a-392d7dffcadc · outbound

This paper cites Model inversion attacks that exploit conﬁdence information and basic countermeasures,.

Local Differential Privacy for Deep Learning Model inversion attacks that exploit conﬁdence information and basic countermeasures,

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T14:36:36.599034Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 70613b5e-630f-4efe-930d-ef6eb88a1a6b · outbound

This paper cites The algorithmic foundations of differential privacy,.

Local Differential Privacy for Deep Learning The algorithmic foundations of differential privacy,

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T14:36:36.582696Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 61f23fc8-266f-4b0b-99c6-fcb28345dfc2 · outbound

This paper cites Privacy-preserving deep learning,.

Local Differential Privacy for Deep Learning Privacy-preserving deep learning,

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T14:36:36.565969Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation a21e6670-d272-4e28-88b1-7352106fdd41 · outbound

This paper cites Output perturbation with query relaxation,.

Local Differential Privacy for Deep Learning Output perturbation with query relaxation,

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T14:36:36.548562Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 30c4759e-b62c-40cc-8911-7795e13153a9 · outbound

This paper cites Extremal mechanisms for local differential privacy,.

Local Differential Privacy for Deep Learning Extremal mechanisms for local differential privacy,

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T14:36:36.530407Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 22d83b17-ba35-4afa-bec8-82c3466b84d8 · outbound

This paper cites an unresolved cited work.

Local Differential Privacy for Deep Learning Unresolved cited work

Reference 11

Resolution: unresolved; raw_fallback, observed 2026-08-14T14:36:36.512950Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 2e3e0e20-5489-4948-b719-8a7d4dbea548 · outbound

This paper cites An efﬁcient and scalable privacy preserving algorithm for big data and data streams,.

Local Differential Privacy for Deep Learning An efﬁcient and scalable privacy preserving algorithm for big data and data streams,

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T14:36:36.496924Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation f96aada3-a78b-4a51-b1d8-6209c3be15c9 · outbound

This paper cites Differentially private continual monitoring of heavy hitters from distributed streams,.

Local Differential Privacy for Deep Learning Differentially private continual monitoring of heavy hitters from distributed streams,

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T14:36:36.481841Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 12b510c9-a6fe-4f31-9641-d5dc71c4a279 · outbound

This paper cites Rappor: Randomized aggre- gatable privacy-preserving ordinal response,.

Local Differential Privacy for Deep Learning Rappor: Randomized aggre- gatable privacy-preserving ordinal response,

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T14:36:36.465818Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation e363f7ad-7d3f-470d-bc7e-51ed06b26e7d · outbound

This paper cites Randomized response: A survey technique for eliminating evasive answer bias,.

Local Differential Privacy for Deep Learning Randomized response: A survey technique for eliminating evasive answer bias,

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-14T14:36:35.615507Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b74c0f5d-3bb0-491e-bd5c-32496990db5e · outbound

This paper cites Using randomized response for differential privacy preserving data collection.

Local Differential Privacy for Deep Learning Using randomized response for differential privacy preserving data collection

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T14:36:36.429825Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation e931c4d9-36ec-4e2b-a851-ab309ba77667 · outbound

This paper cites Heavy hitter estimation over set-valued data with local differential privacy,.

Local Differential Privacy for Deep Learning Heavy hitter estimation over set-valued data with local differential privacy,

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T14:36:36.412869Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 0f83a9f1-bc6e-488e-a628-a296b00c3ec3 · outbound

This paper cites Concentrated differential privacy: Simpliﬁ- cations, extensions, and lower bounds,.

Local Differential Privacy for Deep Learning Concentrated differential privacy: Simpliﬁ- cations, extensions, and lower bounds,

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T14:36:36.397279Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation da092dc1-46cf-478e-bcd3-b01be99909b2 · outbound

This paper cites MVG Mechanism: Differential Privacy under Matrix-Valued Query.

Local Differential Privacy for Deep Learning MVG Mechanism: Differential Privacy under Matrix-Valued Query

Reference 19

Resolution: verified exact; local_arxiv, observed 2026-08-14T14:36:35.916718Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 0e011220-f31d-487b-b6f1-bdd95c33b8b2 · outbound

This paper cites Deep learning in neural networks: An overview,.

Local Differential Privacy for Deep Learning Deep learning in neural networks: An overview,

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-14T14:36:35.640062Z

Source-reported events for the cited work

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Observation b2df6e99-1a37-460b-8e31-53cb2c2ab192 · outbound

This paper cites Convolutional Neural Networks for Sentence Classification.

Local Differential Privacy for Deep Learning Convolutional Neural Networks for Sentence Classification

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-14T14:36:35.645853Z

Source-reported events for the cited work

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Observation 3078e9f0-b421-46a8-9f07-ce37796bf447 · outbound

This paper cites Imagenet classiﬁcation with deep convolutional neural networks,.

Local Differential Privacy for Deep Learning Imagenet classiﬁcation with deep convolutional neural networks,

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-14T14:36:35.651152Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c7a59605-5cc3-423f-bec1-e13eaa36e622 · outbound

This paper cites Finding your way in the fog: Towards a comprehensive deﬁnition of fog computing,.

Local Differential Privacy for Deep Learning Finding your way in the fog: Towards a comprehensive deﬁnition of fog computing,

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T14:36:36.358612Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 47fad5d2-925f-43d7-a860-fa48a68af92e · outbound

This paper cites An Energy-driven Network Function Virtualization for Multi-domain Software Defined Networks.

Local Differential Privacy for Deep Learning An Energy-driven Network Function Virtualization for Multi-domain Software Defined Networks

Reference 24

Resolution: verified exact; local_arxiv, observed 2026-08-14T14:36:35.878992Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 9f03a973-6e80-45be-87c4-cc1d7ce57dba · outbound

This paper cites Keras: Deep learning library for theano and tensor- ﬂow,.

Local Differential Privacy for Deep Learning Keras: Deep learning library for theano and tensor- ﬂow,

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T14:36:36.342452Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 83c07524-0310-438c-a7e4-29f54fa1eb34 · outbound

This paper cites Locally differentially private pro- tocols for frequency estimation,.

Local Differential Privacy for Deep Learning Locally differentially private pro- tocols for frequency estimation,

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T14:36:36.327134Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 3d6944e0-fcff-4595-ba96-3417814a7e6d · outbound

This paper cites Gradient-based learning applied to document recognition,.

Local Differential Privacy for Deep Learning Gradient-based learning applied to document recognition,

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-14T14:36:35.676439Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation bba29ccd-1afe-40e1-8d51-50bf8ee03ae2 · outbound

This paper cites An efﬁcient and ﬁne-grained big data access control scheme with privacy-preserving policy,.

Local Differential Privacy for Deep Learning An efﬁcient and ﬁne-grained big data access control scheme with privacy-preserving policy,

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T14:36:36.298591Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation d06940a0-7678-49c0-bdd9-9cea4c04cd7f · outbound

This paper cites Privacy-preserving record linkage for big data: Current approaches and research challenges,.

Local Differential Privacy for Deep Learning Privacy-preserving record linkage for big data: Current approaches and research challenges,

Reference 29

Resolution: unresolved; no resolver link, observed 2026-08-14T14:36:35.686670Z

Source-reported events for the cited work

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Observation ad364c58-345d-4cef-9df0-ff0c0c6654b0 · outbound

This paper cites A random rotation perturbation approach to privacy preserving data classiﬁcation,.

Local Differential Privacy for Deep Learning A random rotation perturbation approach to privacy preserving data classiﬁcation,

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T14:36:36.266975Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 209d478c-0af1-4b8f-a1f1-3b3732491338 · outbound

This paper cites Geometric data perturbation for privacy preserving outsourced data mining,.

Local Differential Privacy for Deep Learning Geometric data perturbation for privacy preserving outsourced data mining,

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T14:36:36.248221Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 2adef31c-62f1-48b0-a1cb-6c8e530f58d9 · outbound

This paper cites Searchable encryption to reduce encryption degradation in adjustably encrypted databases,.

Local Differential Privacy for Deep Learning Searchable encryption to reduce encryption degradation in adjustably encrypted databases,

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T14:36:36.224154Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 3b19d1d4-8051-4ef0-aa23-baa3b369f61b · outbound

This paper cites Privacy-aware adaptive data encryption strategy of big data in cloud computing,.

Local Differential Privacy for Deep Learning Privacy-aware adaptive data encryption strategy of big data in cloud computing,

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T14:36:36.208557Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 8426b19c-8d99-4b15-8fc8-9a8b1be1ebb9 · outbound

This paper cites Building conﬁdential and efﬁcient query services in the cloud with rasp data perturbation,.

Local Differential Privacy for Deep Learning Building conﬁdential and efﬁcient query services in the cloud with rasp data perturbation,

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T14:36:36.188321Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 53ed0775-2e4f-481c-8b01-3f2d15f6865e · outbound

This paper cites Efﬁcient data perturbation for privacy preserving and accurate data stream mining,.

Local Differential Privacy for Deep Learning Efﬁcient data perturbation for privacy preserving and accurate data stream mining,

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T14:36:36.172632Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 381f09c6-feca-482c-8aea-b65f68d755d4 · outbound

This paper cites Designing statistical privacy for your data,.

Local Differential Privacy for Deep Learning Designing statistical privacy for your data,

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T14:36:36.155789Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation a5706a7d-5f28-477e-9927-5ae7d72cf782 · outbound

This paper cites Efﬁcient privacy preservation of big data for accurate data mining,.

Local Differential Privacy for Deep Learning Efﬁcient privacy preservation of big data for accurate data mining,

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T14:36:36.137460Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 178f837a-3895-43db-b086-ee4b9e2b90e4 · outbound

This paper cites t-closeness: Privacy beyond k-anonymity and l-diversity,.

Local Differential Privacy for Deep Learning t-closeness: Privacy beyond k-anonymity and l-diversity,

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T14:36:36.122283Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation e2f20a89-bef2-47be-a5ba-e1211849ea48 · outbound

This paper cites Information disclosure under realistic assumptions: Privacy versus optimality,.

Local Differential Privacy for Deep Learning Information disclosure under realistic assumptions: Privacy versus optimality,

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T14:36:36.106891Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation b84744ef-f66d-4388-89a2-2fbbc6aad989 · outbound

This paper cites Composition attacks and auxiliary information in data privacy,.

Local Differential Privacy for Deep Learning Composition attacks and auxiliary information in data privacy,

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T14:36:36.091614Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation ff115aa7-b504-4db7-95db-8bd2406a26e9 · outbound

This paper cites Can the utility of anonymized data be used for privacy breaches?.

Local Differential Privacy for Deep Learning Can the utility of anonymized data be used for privacy breaches?

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T14:36:36.074657Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 00860a87-98b3-4d1e-adf7-bfd20d936ab1 · outbound

This paper cites The differential privacy frontier,.

Local Differential Privacy for Deep Learning The differential privacy frontier,

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T14:36:36.058938Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 7060cf78-d278-467e-8dbb-93932a6df031 · outbound

This paper cites Differentially private data release for data mining,.

Local Differential Privacy for Deep Learning Differentially private data release for data mining,

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T14:36:36.029376Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 9cd0f1d9-89c7-4720-81d5-12d368548368 · outbound

This paper cites Towards practical differential privacy for sql queries,.

Local Differential Privacy for Deep Learning Towards practical differential privacy for sql queries,

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T14:36:36.010115Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation edc87a47-16ad-44a3-b003-24ee15e9cbe2 · outbound

This paper cites Privacy integrated queries: an extensible platform for privacy-preserving data analysis,.

Local Differential Privacy for Deep Learning Privacy integrated queries: an extensible platform for privacy-preserving data analysis,

Reference 45

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T14:36:35.991888Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 729e7db0-5371-4174-b7a5-167188aba77e · outbound

This paper cites Local, private, efﬁcient protocols for succinct histograms,.

Local Differential Privacy for Deep Learning Local, private, efﬁcient protocols for succinct histograms,

Reference 46

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T14:36:35.975171Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 58d36571-b3eb-4379-adc9-2f8b15e43d0d · outbound

This paper cites Multi- key privacy-preserving deep learning in cloud computing,.

Local Differential Privacy for Deep Learning Multi- key privacy-preserving deep learning in cloud computing,

Reference 47

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T14:36:35.957814Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 9ab40071-f8bf-4cbf-a762-c1c454236245 · outbound

This paper cites Semi-supervised Knowledge Transfer for Deep Learning from Private Training Data.

Local Differential Privacy for Deep Learning Semi-supervised Knowledge Transfer for Deep Learning from Private Training Data

Reference 48

Resolution: unresolved; no resolver link, observed 2026-08-14T14:36:35.783262Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 69cffede-4b3f-42bd-93d7-ac55a60f6bda · outbound

This paper cites A Hybrid Deep Learning Architecture for Privacy-Preserving Mobile Analytics.

Local Differential Privacy for Deep Learning A Hybrid Deep Learning Architecture for Privacy-Preserving Mobile Analytics

Reference 49

Resolution: unresolved; no resolver link, observed 2026-08-14T14:36:35.788126Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 36460c3b-e8fb-423e-9595-034972b069fe · outbound

This paper cites Scikit-learn: Machine learning in python,.

Local Differential Privacy for Deep Learning Scikit-learn: Machine learning in python,

Reference 50

Resolution: unresolved; no resolver link, observed 2026-08-14T14:36:35.793002Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 07314aa1-8189-4d3a-809c-a6f8e6af016b · outbound

This paper cites Xgboost: A scalable tree boosting system,.

Local Differential Privacy for Deep Learning Xgboost: A scalable tree boosting system,

Reference 51

Resolution: unresolved; no resolver link, observed 2026-08-14T14:36:35.797559Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

No inbound Pith citation observations are available.