Subgraph Counting under Edge Local Differential Privacy Based on Noisy Adjacency Matrix | Paper Citation Record

Observation 98bec6d5-610a-4f6a-8e1a-65e2c26724f6 · outbound

This paper cites Hadamard response: Estimating distributions privately, efficiently, and with little communication.

Subgraph Counting under Edge Local Differential Privacy Based on Noisy Adjacency Matrix Hadamard response: Estimating distributions privately, efficiently, and with little communication

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:10:20.326249Z

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Observation 64f3b419-031a-46e5-aa22-2c96592d8f2e · outbound

This paper cites S., G OULEAKIS , T., PEEBLES , J., R UBINFELD , R., AND YODPINYANEE , A.

Subgraph Counting under Edge Local Differential Privacy Based on Noisy Adjacency Matrix S., G OULEAKIS , T., PEEBLES , J., R UBINFELD , R., AND YODPINYANEE , A

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:10:20.312229Z

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Observation 774dea46-c12e-4958-8949-ed6fcb779350 · outbound

This paper cites Counting triangles in large graphs using ran- domized matrix trace estimation.

Subgraph Counting under Edge Local Differential Privacy Based on Noisy Adjacency Matrix Counting triangles in large graphs using ran- domized matrix trace estimation

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:10:20.298088Z

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Observation 9f0a5173-de71-42f4-a74b-613aaf6f26eb · outbound

This paper cites The privacy blanket of the shuffle model.

Subgraph Counting under Edge Local Differential Privacy Based on Noisy Adjacency Matrix The privacy blanket of the shuffle model

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:10:20.284240Z

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Observation 89b4887c-3f4c-434a-a26c-6e03407a65af · outbound

This paper cites K., AND SESHADHRI , C.

Subgraph Counting under Edge Local Differential Privacy Based on Noisy Adjacency Matrix K., AND SESHADHRI , C

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:10:20.269512Z

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Observation 9aa83368-b493-40b8-8879-9371d186dc30 · outbound

This paper cites W., SCHNEIDER , S., AND KERSCHBAUM , F.

Subgraph Counting under Edge Local Differential Privacy Based on Noisy Adjacency Matrix W., SCHNEIDER , S., AND KERSCHBAUM , F

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:10:20.255878Z

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Observation d12cfdae-70dc-4ab3-8ce8-ec780953d456 · outbound

This paper cites A privacy- preserving mechanism based on local differential pri- vacy in edge computing.

Subgraph Counting under Edge Local Differential Privacy Based on Noisy Adjacency Matrix A privacy- preserving mechanism based on local differential pri- vacy in edge computing

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:10:20.241986Z

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Observation 5ac99d6a-7196-4cc8-b979-ef3fa67802e4 · outbound

This paper cites Approximate counting of k-paths: Deterministic and in polynomial space.

Subgraph Counting under Edge Local Differential Privacy Based on Noisy Adjacency Matrix Approximate counting of k-paths: Deterministic and in polynomial space

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:10:20.228220Z

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Observation ef3cbb5f-305f-432d-b6c4-0e60be63ae80 · outbound

This paper cites Distributed differential privacy via shuf- fling.

Subgraph Counting under Edge Local Differential Privacy Based on Noisy Adjacency Matrix Distributed differential privacy via shuf- fling

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:10:20.214054Z

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Observation 2c0ea86d-42c0-4c10-ade5-288cf3ba170e · outbound

This paper cites Arboricity and sub- graph listing algorithms.

Subgraph Counting under Edge Local Differential Privacy Based on Noisy Adjacency Matrix Arboricity and sub- graph listing algorithms

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:10:20.199080Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 9ac97b1d-fd91-4c3a-abac-f97635ac77a5 · outbound

This paper cites Matrix mul- tiplication via arithmetic progressions.

Subgraph Counting under Edge Local Differential Privacy Based on Noisy Adjacency Matrix Matrix mul- tiplication via arithmetic progressions

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:10:20.184445Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 5a45ae88-30dc-45c6-b65f-e9a7bb7e82ed · outbound

This paper cites an unresolved cited work.

Subgraph Counting under Edge Local Differential Privacy Based on Noisy Adjacency Matrix Unresolved cited work

Reference 12

Resolution: unresolved; raw_fallback, observed 2026-08-06T19:10:20.171009Z

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No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation fc6a1c2e-913a-4bd1-a6bd-63fb236d78a9 · outbound

This paper cites Faster matrix mul- tiplication via asymmetric hashing.

Subgraph Counting under Edge Local Differential Privacy Based on Noisy Adjacency Matrix Faster matrix mul- tiplication via asymmetric hashing

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:10:20.157401Z

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Observation b5a6bec9-0ccd-426b-97ad-50a1a44a3bbc · outbound

This paper cites Differential privacy.

Subgraph Counting under Edge Local Differential Privacy Based on Noisy Adjacency Matrix Differential privacy

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:10:20.143676Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 5195ab32-8932-48c2-92ab-301a77e30b3a · outbound

This paper cites Calibrating noise to sensitivity in private data anal- ysis.

Subgraph Counting under Edge Local Differential Privacy Based on Noisy Adjacency Matrix Calibrating noise to sensitivity in private data anal- ysis

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:10:20.130666Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 43c15dd8-d91b-4215-8784-6590356b1d58 · outbound

This paper cites The algorithmic founda- tions of differential privacy.

Subgraph Counting under Edge Local Differential Privacy Based on Noisy Adjacency Matrix The algorithmic founda- tions of differential privacy

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:10:20.116222Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation f2436c97-5958-4b3a-bfea-9a9b9d475778 · outbound

This paper cites Approximately counting triangles in sublinear time.

Subgraph Counting under Edge Local Differential Privacy Based on Noisy Adjacency Matrix Approximately counting triangles in sublinear time

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:10:20.101664Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 40d4a52c-9c22-4309-9967-a299448a925c · outbound

This paper cites Triangle Counting with Local Edge Differential Privacy.

Subgraph Counting under Edge Local Differential Privacy Based on Noisy Adjacency Matrix Triangle Counting with Local Edge Differential Privacy

Reference 18

Resolution: metadata mismatch; local_arxiv, observed 2026-08-06T19:10:19.499020Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 8f48af87-0abb-448e-be46-a2d04dc9ef41 · outbound

This paper cites Amplification by shuffling: From local to central differential privacy via anonymity.

Subgraph Counting under Edge Local Differential Privacy Based on Noisy Adjacency Matrix Amplification by shuffling: From local to central differential privacy via anonymity

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:10:20.087089Z

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No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation f503929c-9bef-4f7e-b747-6d78ad1701a3 · outbound

This paper cites Hiding among the clones: A simple and nearly opti- mal analysis of privacy amplification by shuffling.

Subgraph Counting under Edge Local Differential Privacy Based on Noisy Adjacency Matrix Hiding among the clones: A simple and nearly opti- mal analysis of privacy amplification by shuffling

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:10:20.073022Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 694d0db7-53a5-48e0-a61f-32de447359c9 · outbound

This paper cites Counting stars and other small subgraphs in sublinear-time.

Subgraph Counting under Edge Local Differential Privacy Based on Noisy Adjacency Matrix Counting stars and other small subgraphs in sublinear-time

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:10:20.058631Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 99b33cdb-e87f-430f-883c-01873b9cd1a2 · outbound

This paper cites Lo- cally differentially private analysis of graph statistics.

Subgraph Counting under Edge Local Differential Privacy Based on Noisy Adjacency Matrix Lo- cally differentially private analysis of graph statistics

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:10:20.044242Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 4a5f2439-5a13-4031-9190-8d40c9101a2a · outbound

This paper cites 983–1000.

Subgraph Counting under Edge Local Differential Privacy Based on Noisy Adjacency Matrix 983–1000

Reference 23

Resolution: parse uncertain; raw_fallback, observed 2026-08-06T19:10:20.029539Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation ff886fb2-f81b-4f72-b29f-1338bd6227a1 · outbound

This paper cites {Communication-Efficient} triangle counting under lo- cal differential privacy.

Subgraph Counting under Edge Local Differential Privacy Based on Noisy Adjacency Matrix {Communication-Efficient} triangle counting under lo- cal differential privacy

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:10:20.014678Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 23544088-ed96-43fc-8652-6cf50f6b092c · outbound

This paper cites Dif- ferentially private triangle and 4-cycle counting in the shuffle model.

Subgraph Counting under Edge Local Differential Privacy Based on Noisy Adjacency Matrix Dif- ferentially private triangle and 4-cycle counting in the shuffle model

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:10:19.999228Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 32081c39-8b29-459b-8217-7bfe3a66e6e2 · outbound

This paper cites Publishing graphs under node differential privacy.

Subgraph Counting under Edge Local Differential Privacy Based on Noisy Adjacency Matrix Publishing graphs under node differential privacy

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:10:19.984583Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 6be7b2ab-bddc-4b9b-b5df-f2a6c90649d0 · outbound

This paper cites Dis- crete distribution estimation under local privacy.

Subgraph Counting under Edge Local Differential Privacy Based on Noisy Adjacency Matrix Dis- crete distribution estimation under local privacy

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:10:19.969612Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation ccb3dc0b-ec93-4cae-b997-792f2df31be7 · outbound

This paper cites The complexity of counting cycles in the adjacency list streaming model.

Subgraph Counting under Edge Local Differential Privacy Based on Noisy Adjacency Matrix The complexity of counting cycles in the adjacency list streaming model

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:10:19.953606Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation f56d67e3-c056-4ec1-b3d1-2bf2919bc6c3 · outbound

This paper cites P., AND KIM, S.

Subgraph Counting under Edge Local Differential Privacy Based on Noisy Adjacency Matrix P., AND KIM, S

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:10:19.939948Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 203eb358-9b48-4c42-8acc-f7a829a9a922 · outbound

This paper cites P., N ISSIM , K., R ASKHOD - NIKOVA , S., AND SMITH , A.

Subgraph Counting under Edge Local Differential Privacy Based on Noisy Adjacency Matrix P., N ISSIM , K., R ASKHOD - NIKOVA , S., AND SMITH , A

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:10:19.925989Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 51c10957-205a-4d42-9874-71aa93a0793a · outbound

This paper cites N., M ILLER , G.

Subgraph Counting under Edge Local Differential Privacy Based on Noisy Adjacency Matrix N., M ILLER , G

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:10:19.911711Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation c081d573-4561-486a-9adc-6af8980784a6 · outbound

This paper cites Powers of tensors and fast matrix multi- plication.

Subgraph Counting under Edge Local Differential Privacy Based on Noisy Adjacency Matrix Powers of tensors and fast matrix multi- plication

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:10:19.898125Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 4c947629-9f3f-45b5-816c-47ee24407003 · outbound

This paper cites Graph evolution: Densification and shrinking diameters.

Subgraph Counting under Edge Local Differential Privacy Based on Noisy Adjacency Matrix Graph evolution: Densification and shrinking diameters

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:10:19.883109Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 7b5584b4-38e4-446f-a7c6-ab2c6867d678 · outbound

This paper cites SNAP Datasets: Stan- ford large network dataset collection.

Subgraph Counting under Edge Local Differential Privacy Based on Noisy Adjacency Matrix SNAP Datasets: Stan- ford large network dataset collection

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:10:19.869359Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation bbec5c9f-d738-41b7-baa6-f7dcf48c2e34 · outbound

This paper cites Learning to dis- cover social circles in ego networks.

Subgraph Counting under Edge Local Differential Privacy Based on Noisy Adjacency Matrix Learning to dis- cover social circles in ego networks

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:10:19.855831Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation f333449b-6d89-4d6c-a644-90990efe0c87 · outbound

This paper cites Collecting triangle counts with edge relationship local differential privacy.

Subgraph Counting under Edge Local Differential Privacy Based on Noisy Adjacency Matrix Collecting triangle counts with edge relationship local differential privacy

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:10:19.842786Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation b1a0ba05-c842-4d13-8af5-c9cde42ad36f · outbound

This paper cites Approximate counting of cycles in streams.

Subgraph Counting under Edge Local Differential Privacy Based on Noisy Adjacency Matrix Approximate counting of cycles in streams

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:10:19.829456Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation b9fafa62-d4a4-4347-bcc4-db9951067767 · outbound

This paper cites Triangle and four cycle counting in the data stream model.

Subgraph Counting under Edge Local Differential Privacy Based on Noisy Adjacency Matrix Triangle and four cycle counting in the data stream model

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:10:19.814418Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 3d51a4a6-9aab-49ef-9c10-ad0b50c7dbdf · outbound

This paper cites an unresolved cited work.

Subgraph Counting under Edge Local Differential Privacy Based on Noisy Adjacency Matrix Unresolved cited work

Reference 39

Resolution: unresolved; raw_fallback, observed 2026-08-06T19:10:19.799970Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 4669150d-7bb3-4a90-a26c-9b1fdda29ef0 · outbound

This paper cites The number of data breaches in 2021 has already surpassed last year’s total, 2021.

Subgraph Counting under Edge Local Differential Privacy Based on Noisy Adjacency Matrix The number of data breaches in 2021 has already surpassed last year’s total, 2021

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:10:19.785819Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 3fbbd61c-2f8c-4836-ab26-3cb612521674 · outbound

This paper cites {Utility- optimized} local differential privacy mechanisms for distribution estimation.

Subgraph Counting under Edge Local Differential Privacy Based on Noisy Adjacency Matrix {Utility- optimized} local differential privacy mechanisms for distribution estimation

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:10:19.771703Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation c0b7364a-df6e-4da4-ba27-f9e313e64a7d · outbound

This paper cites Local and Central Differential Privacy for Robustness and Privacy in Federated Learning.

Subgraph Counting under Edge Local Differential Privacy Based on Noisy Adjacency Matrix Local and Central Differential Privacy for Robustness and Privacy in Federated Learning

Reference 42

Resolution: unresolved; no resolver link, observed 2026-08-06T19:10:19.361450Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 328bcf86-0609-44b9-9cd7-0bd90a607604 · outbound

This paper cites Faster approximate subgraph counts with privacy.

Subgraph Counting under Edge Local Differential Privacy Based on Noisy Adjacency Matrix Faster approximate subgraph counts with privacy

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:10:19.757193Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 57f4f3c8-f326-4e56-ad63-96aadd61fb21 · outbound

This paper cites Smooth sensitivity and sampling in private data anal- ysis.

Subgraph Counting under Edge Local Differential Privacy Based on Noisy Adjacency Matrix Smooth sensitivity and sampling in private data anal- ysis

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:10:19.743335Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation a08866ad-84a4-4d1d-a632-4e390e21be04 · outbound

This paper cites Triangle listing al- gorithms: Back from the diversion.

Subgraph Counting under Edge Local Differential Privacy Based on Noisy Adjacency Matrix Triangle listing al- gorithms: Back from the diversion

Reference 45

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:10:19.729057Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 6c4bb8f1-c1fd-40db-bb31-3bc8ca951185 · outbound

This paper cites Generating synthetic decentralized social graphs with local differential privacy.

Subgraph Counting under Edge Local Differential Privacy Based on Noisy Adjacency Matrix Generating synthetic decentralized social graphs with local differential privacy

Reference 46

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:10:19.715666Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation f40d30c0-c343-4556-b5ba-0beade384baf · outbound

This paper cites Differentially private analysis of graphs.

Subgraph Counting under Edge Local Differential Privacy Based on Noisy Adjacency Matrix Differentially private analysis of graphs

Reference 47

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:10:19.702229Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation c09d4228-c67a-4154-ac3d-b881b0b749e1 · outbound

This paper cites E., A PARICIO , D., AND SILVA, F.

Subgraph Counting under Edge Local Differential Privacy Based on Noisy Adjacency Matrix E., A PARICIO , D., AND SILVA, F

Reference 48

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:10:19.688384Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation eaed251d-cc55-4bf0-85fe-f05ee9bf0fda · outbound

This paper cites an unresolved cited work.

Subgraph Counting under Edge Local Differential Privacy Based on Noisy Adjacency Matrix Unresolved cited work

Reference 49

Resolution: unresolved; raw_fallback, observed 2026-08-06T19:10:19.675401Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 90d6962a-ecbc-4e0f-a275-d15310d3f239 · outbound

This paper cites an unresolved cited work.

Subgraph Counting under Edge Local Differential Privacy Based on Noisy Adjacency Matrix Unresolved cited work

Reference 50

Resolution: unresolved; raw_fallback, observed 2026-08-06T19:10:19.662401Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 93560de0-9265-44fa-933c-0b8890d13ef8 · outbound

This paper cites an unresolved cited work.

Subgraph Counting under Edge Local Differential Privacy Based on Noisy Adjacency Matrix Unresolved cited work

Reference 51

Resolution: unresolved; raw_fallback, observed 2026-08-06T19:10:19.648515Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 998eb9f8-a44f-4ce2-ba34-60d695b98cdc · outbound

This paper cites Gaussian elimination is not optimal.

Subgraph Counting under Edge Local Differential Privacy Based on Noisy Adjacency Matrix Gaussian elimination is not optimal

Reference 52

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:10:19.634649Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation b813027a-08fc-4f1a-9055-4cee7e04a4cd · outbound

This paper cites E., K ANG , U., M ILLER , G.

Subgraph Counting under Edge Local Differential Privacy Based on Noisy Adjacency Matrix E., K ANG , U., M ILLER , G

Reference 53

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:10:19.620585Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 0e3dc45c-bbc8-4be6-a6d6-4389f92a7b2d · outbound

This paper cites an unresolved cited work.

Subgraph Counting under Edge Local Differential Privacy Based on Noisy Adjacency Matrix Unresolved cited work

Reference 54

Resolution: unresolved; raw_fallback, observed 2026-08-06T19:10:19.606270Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 8a3326c0-ccab-420a-b5c9-33672648f4d3 · outbound

This paper cites Locally differentially private protocols for frequency estimation.

Subgraph Counting under Edge Local Differential Privacy Based on Noisy Adjacency Matrix Locally differentially private protocols for frequency estimation

Reference 55

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:10:19.591873Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 15337bc7-64bb-437a-b393-c6e51ce897eb · outbound

This paper cites Edge-based differential privacy comput- ing for sensor–cloud systems.

Subgraph Counting under Edge Local Differential Privacy Based on Noisy Adjacency Matrix Edge-based differential privacy comput- ing for sensor–cloud systems

Reference 56

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:10:19.576605Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 94be922f-2957-47a0-800f-4378c96cd8c0 · outbound

This paper cites Using randomized response for differential privacy preserving data col- lection.

Subgraph Counting under Edge Local Differential Privacy Based on Noisy Adjacency Matrix Using randomized response for differential privacy preserving data col- lection

Reference 57

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:10:19.561086Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation e5bb9d94-9ae0-47cd-b792-fbb2cbb02e07 · outbound

This paper cites an unresolved cited work.

Subgraph Counting under Edge Local Differential Privacy Based on Noisy Adjacency Matrix Unresolved cited work

Reference 58

Resolution: unresolved; raw_fallback, observed 2026-08-06T19:10:19.544694Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 036f43fd-06ee-45a5-9ae9-9d6c6210d063 · outbound

This paper cites an unresolved cited work.

Subgraph Counting under Edge Local Differential Privacy Based on Noisy Adjacency Matrix Unresolved cited work

Reference 59

Resolution: unresolved; raw_fallback, observed 2026-08-06T19:10:19.529390Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation b1de0fd1-621c-43a3-b99d-03a22ee73e83 · outbound

This paper cites n1 ∏ i=1 Zki αi #2 + E.

Subgraph Counting under Edge Local Differential Privacy Based on Noisy Adjacency Matrix n1 ∏ i=1 Zki αi #2 + E

Reference 60

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:10:19.514574Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Coverage vector

Reference resolution

Outbound references

Pith citing papers