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Paper Citation Record · LEDGER

Achieving Hilbert-Schmidt Independence Under R\'enyi Differential Privacy for Fair and Private Data Generation

As of 9 August 2026, this Paper Citation Record lists 29 of 29 outbound references and 0 inbound Pith citation observations for arXiv:2508.21815.

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

pith.paper-citation-record.v1
2508.21815 v1

Coverage vector

measured 29 of 29 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-05T13:59:46.344430Z

measured 29 of 29 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+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

29 of 29 outbound references displayed

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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 69156578-646e-47a7-8e38-fd188069b091 · outbound

This paper cites Deep learning with differential privacy.

Achieving Hilbert-Schmidt Independence Under R\'enyi Differential Privacy for Fair and Private Data Generation Deep learning with differential privacy

Reference 1

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verified fuzzy
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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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Observation 20657caf-e79d-4190-8dcf-590e17581419 · outbound

This paper cites Barry Becker and Ronny Kohavi.

Achieving Hilbert-Schmidt Independence Under R\'enyi Differential Privacy for Fair and Private Data Generation Barry Becker and Ronny Kohavi

Reference 3

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation f8ad30dc-fd42-4011-a42c-db29675dd854 · outbound

This paper cites European Parliament and Council of the European Union.

Achieving Hilbert-Schmidt Independence Under R\'enyi Differential Privacy for Fair and Private Data Generation European Parliament and Council of the European Union

Reference 8

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verified fuzzy
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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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Observation bbec7084-c306-4ce9-bbcc-36a03ecadd99 · outbound

This paper cites Mei Ling Fang, Devendra Singh Dhami, and Kristian Kersting.

Achieving Hilbert-Schmidt Independence Under R\'enyi Differential Privacy for Fair and Private Data Generation Mei Ling Fang, Devendra Singh Dhami, and Kristian Kersting

Reference 9

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verified fuzzy
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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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Observation 29df3e2c-6931-4cad-835c-176b9f939744 · outbound

This paper cites doi: 10.1016/j.mlwa.2024.100608.

Achieving Hilbert-Schmidt Independence Under R\'enyi Differential Privacy for Fair and Private Data Generation doi: 10.1016/j.mlwa.2024.100608

Reference 12

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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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Observation 14212a92-a7ff-4a2e-b85d-8333069e704b · outbound

This paper cites Kingma and Max Welling.

Achieving Hilbert-Schmidt Independence Under R\'enyi Differential Privacy for Fair and Private Data Generation Kingma and Max Welling

Reference 13

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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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Observation 1e1bc9c2-a0b5-44ae-a302-72de5ff42596 · outbound

This paper cites Auto-Encoding Variational Bayes.

Achieving Hilbert-Schmidt Independence Under R\'enyi Differential Privacy for Fair and Private Data Generation Auto-Encoding Variational Bayes

Reference 14

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation d4a6d3c2-9795-401f-b835-932627820cd0 · outbound

This paper cites doi: 10.1145/3704437.

Achieving Hilbert-Schmidt Independence Under R\'enyi Differential Privacy for Fair and Private Data Generation doi: 10.1145/3704437

Reference 16

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unresolved
no resolver link, observed 2026-08-05T13:59:45.244768Z

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Unavailable: canonical work link unavailable.

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Observation 94d276f4-31c3-4bea-972e-2a691fec8b97 · outbound

This paper cites ISBN 9781450390965.

Achieving Hilbert-Schmidt Independence Under R\'enyi Differential Privacy for Fair and Private Data Generation ISBN 9781450390965

Reference 18

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Unavailable: canonical work link unavailable.

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Observation b8a20f18-7f03-45e7-81e7-7d3318c289dd · outbound

This paper cites doi: 10.14778/ 3583140.3583168.

Achieving Hilbert-Schmidt Independence Under R\'enyi Differential Privacy for Fair and Private Data Generation doi: 10.14778/ 3583140.3583168

Reference 22

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Observation 8a2e2954-9bdd-4b8b-be8a-f0cc4f45370e · outbound

This paper cites doi: 10.3390/make4020022.

Achieving Hilbert-Schmidt Independence Under R\'enyi Differential Privacy for Fair and Private Data Generation doi: 10.3390/make4020022

Reference 23

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verified exact
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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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Observation 01504750-bc1c-4e4a-a96e-6f1e6a4f71e9 · outbound

This paper cites TabularARGN: A Flexible and Efficient Auto-Regressive Framework for Generating High-Fidelity Synthetic Data.

Achieving Hilbert-Schmidt Independence Under R\'enyi Differential Privacy for Fair and Private Data Generation TabularARGN: A Flexible and Efficient Auto-Regressive Framework for Generating High-Fidelity Synthetic Data

Reference 24

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unresolved
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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation de632386-db60-4b7d-a506-0e11e61b8c4c · outbound

This paper cites doi: 10.1016/j.ins.2021.12.018.

Achieving Hilbert-Schmidt Independence Under R\'enyi Differential Privacy for Fair and Private Data Generation doi: 10.1016/j.ins.2021.12.018

Reference 25

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Observation 850cf8b1-bb3f-4dab-ae5b-d3eb64d3b7c5 · outbound

This paper cites Shuai Wang, Paul Verhagen, Jennifer Zhuge, and Velizar Shulev.

Achieving Hilbert-Schmidt Independence Under R\'enyi Differential Privacy for Fair and Private Data Generation Shuai Wang, Paul Verhagen, Jennifer Zhuge, and Velizar Shulev

Reference 27

Resolution
verified fuzzy
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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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Observation 9c803bdc-7e63-4a2a-8c74-17452adef764 · outbound

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

Achieving Hilbert-Schmidt Independence Under R\'enyi Differential Privacy for Fair and Private Data Generation Opacus: User-Friendly Differential Privacy Library in PyTorch

Reference 30

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation c4b74bef-4afb-4950-8b27-f59075af64e9 · outbound

This paper cites Irina Higgins, Loic Matthey, Arka Pal, Christopher Burgess, Xavier Glorot, Matthew Botvinick, Shakir Mohamed, and Alexander Lerchner.

Achieving Hilbert-Schmidt Independence Under R\'enyi Differential Privacy for Fair and Private Data Generation Irina Higgins, Loic Matthey, Arka Pal, Christopher Burgess, Xavier Glorot, Matthew Botvinick, Shakir Mohamed, and Alexander Lerchner

Reference 1971

Resolution
verified exact
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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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Observation c77e10e6-609f-4ca6-acd5-2545a48ed62a · outbound

This paper cites ISBN 978-3-540-32732-5.

Achieving Hilbert-Schmidt Independence Under R\'enyi Differential Privacy for Fair and Private Data Generation ISBN 978-3-540-32732-5

Reference 2006

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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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Observation e92c529c-3c45-47bd-bc8e-cd16e7484dce · outbound

This paper cites doi: 10.1561/0400000042.

Achieving Hilbert-Schmidt Independence Under R\'enyi Differential Privacy for Fair and Private Data Generation doi: 10.1561/0400000042

Reference 2014

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Unavailable: canonical work link unavailable.

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Observation 1961acd3-edf4-446f-9525-62500e87e223 · outbound

This paper cites ISBN 9781450336642.

Achieving Hilbert-Schmidt Independence Under R\'enyi Differential Privacy for Fair and Private Data Generation ISBN 9781450336642

Reference 2015

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation a02bba3c-bee0-4b48-a303-b6d98d6e73fd · outbound

This paper cites ISBN 9781450341394.

Achieving Hilbert-Schmidt Independence Under R\'enyi Differential Privacy for Fair and Private Data Generation ISBN 9781450341394

Reference 2016

Resolution
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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation e91ce5e9-05e8-4fc3-be6e-fad6ea66ae83 · outbound

This paper cites Yujin Choi, Jinseong Park, Hoki Kim, Jaewook Lee, and Saerom Park.

Achieving Hilbert-Schmidt Independence Under R\'enyi Differential Privacy for Fair and Private Data Generation Yujin Choi, Jinseong Park, Hoki Kim, Jaewook Lee, and Saerom Park

Reference 2017

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verified fuzzy
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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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Observation 2164a7cf-4c6b-4ba8-a570-1e79bf5816f6 · outbound

This paper cites Differentially Private Generative Adversarial Network.

Achieving Hilbert-Schmidt Independence Under R\'enyi Differential Privacy for Fair and Private Data Generation Differentially Private Generative Adversarial Network

Reference 2018

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Unavailable: canonical work link unavailable.

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Observation 177ace3e-e7bf-46d1-bff6-4b1d11227e09 · outbound

This paper cites R\'enyi Differential Privacy of the Sampled Gaussian Mechanism.

Achieving Hilbert-Schmidt Independence Under R\'enyi Differential Privacy for Fair and Private Data Generation R\'enyi Differential Privacy of the Sampled Gaussian Mechanism

Reference 2019

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 8f924057-4120-4394-8a0a-8186873d8a28 · outbound

This paper cites doi: 10.1109/JBHI.2020.2980262.

Achieving Hilbert-Schmidt Independence Under R\'enyi Differential Privacy for Fair and Private Data Generation doi: 10.1109/JBHI.2020.2980262

Reference 2020

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metadata mismatch
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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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Observation 519f1a2e-5ff1-49a3-acf8-1ac2b69931da · outbound

This paper cites P Van Der Laan.

Achieving Hilbert-Schmidt Independence Under R\'enyi Differential Privacy for Fair and Private Data Generation P Van Der Laan

Reference 2021

Resolution
verified fuzzy
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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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Observation 75409332-9b21-4246-a207-e46c2acd77b9 · outbound

This paper cites FairGAN: Gans-based fairness-aware learning for recommendations with implicit feedback.

Achieving Hilbert-Schmidt Independence Under R\'enyi Differential Privacy for Fair and Private Data Generation FairGAN: Gans-based fairness-aware learning for recommendations with implicit feedback

Reference 2022

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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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Observation 0df5a23c-1bd7-42fd-b056-df85d99672b0 · outbound

This paper cites Cited by: 24; All Open Access, Green Open Access.

Achieving Hilbert-Schmidt Independence Under R\'enyi Differential Privacy for Fair and Private Data Generation Cited by: 24; All Open Access, Green Open Access

Reference 2023

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Source-reported events for the cited work

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Observation c71da0cc-15d9-43a2-94ab-5bb07e155316 · outbound

This paper cites URL https://ojs.aaai.org/index.php/ AAAI/article/view/30202.

Achieving Hilbert-Schmidt Independence Under R\'enyi Differential Privacy for Fair and Private Data Generation URL https://ojs.aaai.org/index.php/ AAAI/article/view/30202

Reference 2024

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verified exact
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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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Observation 48deb71a-c477-43a2-b214-3568cb20ff34 · outbound

This paper cites Simon Kornblith, Mohammad Norouzi, Honglak Lee, and Geoffrey Hinton.

Achieving Hilbert-Schmidt Independence Under R\'enyi Differential Privacy for Fair and Private Data Generation Simon Kornblith, Mohammad Norouzi, Honglak Lee, and Geoffrey Hinton

Reference 2025

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metadata mismatch
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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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Pith citing papers

No inbound Pith citation observations are available.