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Paper Citation Record · LEDGER

Fundamental Limits of Query-Based Subgraph Detection

As of 14 August 2026, this Paper Citation Record lists 100 of 300 outbound references and 0 inbound Pith citation observations for arXiv:2607.17118.

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

pith.paper-citation-record.v1
2607.17118 v1

Coverage vector

measured 100 of 300 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-01T19:10:23.858378Z

measured 100 of 100 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-14T06:32:32.682623+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

100 of 300 outbound references displayed

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External citation measurements

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Outbound references

Observation 2394e30c-38e4-4d27-b8a2-ac4f2b6ce8e8 · outbound

This paper cites Statistical-computational tradeoffs in planted problems and submatrix localization with a growing number of clusters and submatrices , Volume =.

Fundamental Limits of Query-Based Subgraph Detection Statistical-computational tradeoffs in planted problems and submatrix localization with a growing number of clusters and submatrices , Volume =

Reference 1

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Observation e69aa119-edc2-4350-8c05-742482c1db67 · outbound

This paper cites In Proceedings of the 31st Conference On Learning Theory , volume =.

Fundamental Limits of Query-Based Subgraph Detection In Proceedings of the 31st Conference On Learning Theory , volume =

Reference 2

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Observation c8e740cf-342a-4ee4-b652-38b905442a35 · outbound

This paper cites In Proceedings of The 28th Conference on Learning Theory , volume =.

Fundamental Limits of Query-Based Subgraph Detection In Proceedings of The 28th Conference on Learning Theory , volume =

Reference 3

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Observation a8602cd5-b488-493f-bac4-a12a70ce296d · outbound

This paper cites Proceedings of the Thirty Eighth Conference on Learning Theory , series =.

Fundamental Limits of Query-Based Subgraph Detection Proceedings of the Thirty Eighth Conference on Learning Theory , series =

Reference 4

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Observation 49d95653-87e8-443d-8176-395c8261cbc1 · outbound

This paper cites IEEE Transactions on Signal and Information Processing over Networks , volume =.

Fundamental Limits of Query-Based Subgraph Detection IEEE Transactions on Signal and Information Processing over Networks , volume =

Reference 5

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Observation bd2ee05f-da37-4e09-8130-4fd6760b9d53 · outbound

This paper cites Proceedings of the Thirty-Second Conference on Learning Theory , pages =.

Fundamental Limits of Query-Based Subgraph Detection Proceedings of the Thirty-Second Conference on Learning Theory , pages =

Reference 6

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Observation c5082123-f8ff-423f-8ed7-3c3ceb971363 · outbound

This paper cites Random Structures & Algorithms , volume=.

Fundamental Limits of Query-Based Subgraph Detection Random Structures & Algorithms , volume=

Reference 7

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Observation c756b1b5-923f-491b-a532-d3a5bddf4fb4 · outbound

This paper cites Testing k-wise and almost k-wise independence , Year =.

Fundamental Limits of Query-Based Subgraph Detection Testing k-wise and almost k-wise independence , Year =

Reference 8

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Observation e7704f13-3aaa-4d86-88ed-4068df52c5a1 · outbound

This paper cites Computational and statistical boundaries for submatrix localization in a large noisy matrix.

Fundamental Limits of Query-Based Subgraph Detection Computational and statistical boundaries for submatrix localization in a large noisy matrix

Reference 9

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Observation 91b78903-17ab-47f2-8adc-4f46e4ddaac0 · outbound

This paper cites Sparse pca via covariance thresholding , Year =.

Fundamental Limits of Query-Based Subgraph Detection Sparse pca via covariance thresholding , Year =

Reference 10

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Observation 175ae32a-1723-4b89-8a64-fbdf719513ae · outbound

This paper cites Large cliques elude the Metropolis process , Volume =.

Fundamental Limits of Query-Based Subgraph Detection Large cliques elude the Metropolis process , Volume =

Reference 11

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Observation 78a3bfbc-a038-40ff-9726-ee9bf989192f · outbound

This paper cites Finite exchangeable sequences , Year =.

Fundamental Limits of Query-Based Subgraph Detection Finite exchangeable sequences , Year =

Reference 12

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Observation d684e22a-c056-498f-b9dc-51688004eda6 · outbound

This paper cites Finding hidden cliques of size.

Fundamental Limits of Query-Based Subgraph Detection Finding hidden cliques of size

Reference 13

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Observation 0cae9d72-6c59-4191-854a-faac353eb01a · outbound

This paper cites Using More Data to Speed-up Training Time.

Fundamental Limits of Query-Based Subgraph Detection Using More Data to Speed-up Training Time

Reference 14

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Observation e98c6ec7-99d3-422e-8f93-27d226d676d1 · outbound

This paper cites Bulletin of the American Mathematical Society , number =.

Fundamental Limits of Query-Based Subgraph Detection Bulletin of the American Mathematical Society , number =

Reference 15

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Observation f1179abf-450f-403d-b707-b309645f4e59 · outbound

This paper cites Minimax Rates of Estimation for Sparse PCA in High Dimensions.

Fundamental Limits of Query-Based Subgraph Detection Minimax Rates of Estimation for Sparse PCA in High Dimensions

Reference 16

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Observation 600d73cd-bb8a-4d9a-9aae-9d6272c9aa8a · outbound

This paper cites Do semidefinite relaxations solve sparse PCA up to the information limit? , Volume =.

Fundamental Limits of Query-Based Subgraph Detection Do semidefinite relaxations solve sparse PCA up to the information limit? , Volume =

Reference 17

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Observation e106841a-51bc-4531-9a6c-482a96d528f7 · outbound

This paper cites Phase transition of the largest eigenvalue for nonnull complex sample covariance matrices , Volume =.

Fundamental Limits of Query-Based Subgraph Detection Phase transition of the largest eigenvalue for nonnull complex sample covariance matrices , Volume =

Reference 18

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Observation 9b7a1f83-72c5-4824-add5-e4829d7bfd0a · outbound

This paper cites Regularized estimation of large covariance matrices , Year =.

Fundamental Limits of Query-Based Subgraph Detection Regularized estimation of large covariance matrices , Year =

Reference 19

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Observation d2fd5d3b-b6c8-4d0d-af57-dab310208d10 · outbound

This paper cites Adaptive thresholding for sparse covariance matrix estimation , Volume =.

Fundamental Limits of Query-Based Subgraph Detection Adaptive thresholding for sparse covariance matrix estimation , Volume =

Reference 20

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Observation f8d50894-96f2-4373-9022-ab2bba7cdf78 · outbound

This paper cites On information plus noise kernel random matrices , Volume =.

Fundamental Limits of Query-Based Subgraph Detection On information plus noise kernel random matrices , Volume =

Reference 21

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Observation 0bc62f6e-ebd8-4f19-a9a7-502c5f7afdbb · outbound

This paper cites Optimal solutions for sparse principal component analysis , Volume =.

Fundamental Limits of Query-Based Subgraph Detection Optimal solutions for sparse principal component analysis , Volume =

Reference 22

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Observation 89245ca7-256c-4838-9350-64c6df1ea7d4 · outbound

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Fundamental Limits of Query-Based Subgraph Detection Unpublished manuscript , Title =

Reference 23

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Observation bbfd25ea-6ca1-4d30-b80f-5ff706741d95 · outbound

This paper cites Asymptotics of sample eigenstructure for a large dimensional spiked covariance model , Year =.

Fundamental Limits of Query-Based Subgraph Detection Asymptotics of sample eigenstructure for a large dimensional spiked covariance model , Year =

Reference 24

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Observation 0c0ae085-2212-43c5-9ef3-f401eb0c038d · outbound

This paper cites Detecting positive correlations in a multivariate sample , Volume =.

Fundamental Limits of Query-Based Subgraph Detection Detecting positive correlations in a multivariate sample , Volume =

Reference 25

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Observation 37118b69-c082-4f38-a495-39e63f298203 · outbound

This paper cites Detection of correlations , Volume =.

Fundamental Limits of Query-Based Subgraph Detection Detection of correlations , Volume =

Reference 26

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Observation efd683fa-663c-4b29-a39a-b68f24ce8c6b · outbound

This paper cites On combinatorial testing problems , Volume =.

Fundamental Limits of Query-Based Subgraph Detection On combinatorial testing problems , Volume =

Reference 27

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Observation d60ec69b-c321-4eea-9a45-2217a4866354 · outbound

This paper cites Finding a large hidden clique in a random graph , Volume =.

Fundamental Limits of Query-Based Subgraph Detection Finding a large hidden clique in a random graph , Volume =

Reference 28

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Observation 1bc6c1b1-24dd-45ce-85a6-b367dcd8a1c8 · outbound

This paper cites High-dimensional analysis of semidefinite relaxations for sparse principal components , Volume =.

Fundamental Limits of Query-Based Subgraph Detection High-dimensional analysis of semidefinite relaxations for sparse principal components , Volume =

Reference 29

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Observation 8bc05c53-94df-4350-9eaa-64e6b13849c5 · outbound

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Fundamental Limits of Query-Based Subgraph Detection Detection of a sparse submatrix of a high-dimensional noisy matrix , Volume =

Reference 30

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Observation d7c97d8f-e863-444d-b319-189189e40328 · outbound

This paper cites Computational and statistical tradeoffs via convex relaxation , Volume =.

Fundamental Limits of Query-Based Subgraph Detection Computational and statistical tradeoffs via convex relaxation , Volume =

Reference 31

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Observation b105b8e8-5b1c-45de-9ef5-1234876638bd · outbound

This paper cites A Direct Formulation for Sparse PCA Using Semidefinite Programming.

Fundamental Limits of Query-Based Subgraph Detection A Direct Formulation for Sparse PCA Using Semidefinite Programming

Reference 32

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Observation 0d29c6b0-bf1e-41aa-8ad0-8deb7b51e526 · outbound

This paper cites Optimal rates of convergence for covariance matrix estimation , Volume =.

Fundamental Limits of Query-Based Subgraph Detection Optimal rates of convergence for covariance matrix estimation , Volume =

Reference 33

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Observation 964c6659-14b4-447b-b4a7-d42ea4f04d70 · outbound

This paper cites On consistency and sparsity for principal components analysis in high dimensions , Volume =.

Fundamental Limits of Query-Based Subgraph Detection On consistency and sparsity for principal components analysis in high dimensions , Volume =

Reference 34

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Observation 49931576-997d-471a-ab0d-d2266b79667f · outbound

This paper cites Distribution-free Detection of a Submatrix.

Fundamental Limits of Query-Based Subgraph Detection Distribution-free Detection of a Submatrix

Reference 35

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Fundamental Limits of Query-Based Subgraph Detection Wein , Journal =

Reference 36

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Observation 84361462-da15-4c62-9150-9b74f8824f19 · outbound

This paper cites Resource Allocation for Statistical Estimation , Volume =.

Fundamental Limits of Query-Based Subgraph Detection Resource Allocation for Statistical Estimation , Volume =

Reference 37

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Observation 0a1b2618-02d7-4567-aadd-16017108ed53 · outbound

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Fundamental Limits of Query-Based Subgraph Detection Optimal Rates of Statistical Seriation

Reference 38

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Observation 9f724f6e-3fb4-4925-904c-6b7fcf99799a · outbound

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Fundamental Limits of Query-Based Subgraph Detection Volume ratio, sparsity, and minimaxity under unitarily invariant norms , Volume =

Reference 39

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source=arxiv_source observed=2026-08-01T19:10:17.930130Z digest=sha256:6546a6c1340b56a7a47f3380679a416d6dd7d44b4063e21f18e953d6d4a8d588

Observation 63a863ee-3ff1-40ac-8f15-ddf2af49dc39 · outbound

This paper cites Sparse PCA via Covariance Thresholding , Volume =.

Fundamental Limits of Query-Based Subgraph Detection Sparse PCA via Covariance Thresholding , Volume =

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source=arxiv_source observed=2026-08-01T19:10:17.997648Z digest=sha256:c8da6dca48a06a3c5ccd43da623dc47f203f002d49783d6725d8188714316961

Observation 625df5c8-6980-4320-b625-c9dca7f96099 · outbound

This paper cites Lower bounds on the performance of polynomial-time algorithms for sparse linear regression.

Fundamental Limits of Query-Based Subgraph Detection Lower bounds on the performance of polynomial-time algorithms for sparse linear regression

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source=arxiv_source observed=2026-08-01T19:10:18.055348Z digest=sha256:9223fc0badadd84bcb1c3629600a4a033f7020d2f2d625605fe86675a4664f92

Observation ff2b2482-b137-4f86-82d2-a627e447e206 · outbound

This paper cites Sparse principal component analysis and iterative thresholding , Volume =.

Fundamental Limits of Query-Based Subgraph Detection Sparse principal component analysis and iterative thresholding , Volume =

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source=arxiv_source observed=2026-08-01T19:10:18.125201Z digest=sha256:05250df18fc06ba0869f08361ab5b959f88444cc40baccd08d178cbef8f6821d

Observation 73d6f4a9-358f-4938-ad6f-67df798ea74a · outbound

This paper cites Optimal Shrinkage of Eigenvalues in the Spiked Covariance Model.

Fundamental Limits of Query-Based Subgraph Detection Optimal Shrinkage of Eigenvalues in the Spiked Covariance Model

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source=arxiv_source observed=2026-08-01T19:10:18.196387Z digest=sha256:814950db00a84d17162a7ba9f7d603f87b9ce5393a37ea345357eebab647b268

Observation 49bbb9a5-7843-4afc-a119-d3262521bf5d · outbound

This paper cites Testing in high-dimensional spiked models.

Fundamental Limits of Query-Based Subgraph Detection Testing in high-dimensional spiked models

Reference 44

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source=arxiv_source observed=2026-08-01T19:10:18.273566Z digest=sha256:09a1e549c245d0c96c5e61fae6b3271c0c6d5802a3716454785b3ae64cad6ce7

Observation 2ccc7b84-2ba3-49b3-acff-77d72fea4cfb · outbound

This paper cites Joint density of eigenvalues in spiked multivariate models , Volume =.

Fundamental Limits of Query-Based Subgraph Detection Joint density of eigenvalues in spiked multivariate models , Volume =

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source=arxiv_source observed=2026-08-01T19:10:18.361870Z digest=sha256:1f382bc72efd6976d23a7ca0e003cc73b3377dbf3822e56eb10c3216724011f4

Observation a5dcc946-fb9d-4c1b-b8a7-668bafc08d05 · outbound

This paper cites Testing for high-dimensional geometry in random graphs , Year =.

Fundamental Limits of Query-Based Subgraph Detection Testing for high-dimensional geometry in random graphs , Year =

Reference 46

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source=arxiv_source observed=2026-08-01T19:10:18.427005Z digest=sha256:96064c1bca4cf0cfb7d8dfa2c68eab8aee6d929a286b37c83d445951d7d5629b

Observation 01362d76-c3f3-4fb8-bdaa-406163ff1fd0 · outbound

This paper cites Minimax estimation in sparse canonical correlation analysis , Volume =.

Fundamental Limits of Query-Based Subgraph Detection Minimax estimation in sparse canonical correlation analysis , Volume =

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source=arxiv_source observed=2026-08-01T19:10:18.472659Z digest=sha256:16ed584ffb729252df387691f37dce9afe54ff925ce91999069cec30e1ba2a08

Observation ea45554d-f52a-4a14-b93d-dca97a29d27e · outbound

This paper cites Sum-of-squares lower bounds for sparse pca , Year =.

Fundamental Limits of Query-Based Subgraph Detection Sum-of-squares lower bounds for sparse pca , Year =

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source=arxiv_source observed=2026-08-01T19:10:18.518125Z digest=sha256:0a239970cd3e8c36bbfe91ed2c85aebe6ef37bd27c9cc5c9e85feb986246d7d9

Observation 571a33d3-188c-4725-9a8b-2244638a7e84 · outbound

This paper cites ETH hardness for densest-k-subgraph with perfect completeness , Year =.

Fundamental Limits of Query-Based Subgraph Detection ETH hardness for densest-k-subgraph with perfect completeness , Year =

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source=arxiv_source observed=2026-08-01T19:10:18.583444Z digest=sha256:71f249a974ce8ad0a64302d15962a8e5adad7f8a01291861ffb689fee34cb16c

Observation e3f45498-557b-402b-9a35-27e6c8d5c1dc · outbound

This paper cites On the limitation of spectral methods: From the gaussian hidden clique problem to rank-one perturbations of gaussian tensors , Year =.

Fundamental Limits of Query-Based Subgraph Detection On the limitation of spectral methods: From the gaussian hidden clique problem to rank-one perturbations of gaussian tensors , Year =

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source=arxiv_source observed=2026-08-01T19:10:18.633907Z digest=sha256:cb020d0455d9434f2cb3d9fe317007429416f9cf5c5fba555438efb4c35264f5

Observation 0fc696a1-1564-4704-b739-a0901c5e5f47 · outbound

This paper cites Tensor principal component analysis via sum-of-square proofs.

Fundamental Limits of Query-Based Subgraph Detection Tensor principal component analysis via sum-of-square proofs

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source=arxiv_source observed=2026-08-01T19:10:18.726215Z digest=sha256:e39f4e6e31a90bb79abe433e2a50d961923d9fe7aa4679438c430149b45419b4

Observation 32b0bb4a-ea30-4cfc-b161-f413b893283a · outbound

This paper cites Computational Limits for Matrix Completion.

Fundamental Limits of Query-Based Subgraph Detection Computational Limits for Matrix Completion

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source=arxiv_source observed=2026-08-01T19:10:18.731398Z digest=sha256:d6980eeaef0a8f81d17f981a622940a92dfdc46d1299d136244d99c3a484a2e7

Observation f92c5d66-b71d-4464-84da-5e6981cedc36 · outbound

This paper cites Optimal rates of convergence for noisy sparse phase retrieval via thresholded Wirtinger flow , Volume =.

Fundamental Limits of Query-Based Subgraph Detection Optimal rates of convergence for noisy sparse phase retrieval via thresholded Wirtinger flow , Volume =

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source=arxiv_source observed=2026-08-01T19:10:18.736328Z digest=sha256:dee5f4ee1fabd8cdfa20ebec181574193f996d6916d905d96cc044b0049bafdc

Observation 45f6da5f-b367-4d71-9783-d871057890e9 · outbound

This paper cites Proceedings of The 28th Conference on Learning Theory , pages =.

Fundamental Limits of Query-Based Subgraph Detection Proceedings of The 28th Conference on Learning Theory , pages =

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source=arxiv_source observed=2026-08-01T19:10:18.815615Z digest=sha256:0498e6ed1a42ab3b8667869ecf76289f7a2071216006a2b3b42d7ada9fadbd27

Observation fd66b44c-5f94-4d27-8e30-f3d332dac7c6 · outbound

This paper cites Optimal estimation and rank detection for sparse spiked covariance matrices , Volume =.

Fundamental Limits of Query-Based Subgraph Detection Optimal estimation and rank detection for sparse spiked covariance matrices , Volume =

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source=arxiv_source observed=2026-08-01T19:10:18.892159Z digest=sha256:0fb4030417f1d21a247febbf55d9ffbdec45dd7196be5d35b399d399dc38a1a9

Observation bbd03cdf-ab36-41f6-86ee-b10a65e4db8d · outbound

This paper cites Computational barriers in minimax submatrix detection , Volume =.

Fundamental Limits of Query-Based Subgraph Detection Computational barriers in minimax submatrix detection , Volume =

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source=arxiv_source observed=2026-08-01T19:10:18.976457Z digest=sha256:29ca07bc67907d7e182734560d0551d33cb45ef86bdb6616107d8ddea8e5ad70

Observation da9002eb-ea9e-4956-a254-997b90cd2e93 · outbound

This paper cites Estimation of functionals of sparse covariance matrices , Volume =.

Fundamental Limits of Query-Based Subgraph Detection Estimation of functionals of sparse covariance matrices , Volume =

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source=arxiv_source observed=2026-08-01T19:10:19.062299Z digest=sha256:22ba5dca2cfde090cc1a04ab2d7e7692ce38bba0e4ba4cbb222666a678c85c87

Observation 090ad9c6-0f54-4ccc-8c09-15aac5ab82b7 · outbound

This paper cites Average-case hardness of RIP certification , Year =.

Fundamental Limits of Query-Based Subgraph Detection Average-case hardness of RIP certification , Year =

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source=arxiv_source observed=2026-08-01T19:10:19.180609Z digest=sha256:9f7abd7ac96c31c71661bcd27399c855af00d2e1b71f85230028ab8c6b00e32b

Observation 1667d7b9-e664-4324-a8a8-b803e6510453 · outbound

This paper cites Statistical and computational trade-offs in estimation of sparse principal components , Volume =.

Fundamental Limits of Query-Based Subgraph Detection Statistical and computational trade-offs in estimation of sparse principal components , Volume =

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source=arxiv_source observed=2026-08-01T19:10:19.313043Z digest=sha256:d3c492547132484cfde706be07c4ca45ec892784c6a440ae941ec67ac6bf95f1

Observation df30e6eb-7816-40d0-af93-8eaf7127b735 · outbound

This paper cites Optimal detection of sparse principal components in high dimension , Volume =.

Fundamental Limits of Query-Based Subgraph Detection Optimal detection of sparse principal components in high dimension , Volume =

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source=arxiv_source observed=2026-08-01T19:10:19.462199Z digest=sha256:61b493f54677fe2d5be4cfce775ced0ba411b7e6b58600b38b9e8a26d7984ab9

Observation c80f59fe-6f8c-4e67-98af-14ee8269a15e · outbound

This paper cites Proceedings of the 26th Annual Conference on Learning Theory , pages =.

Fundamental Limits of Query-Based Subgraph Detection Proceedings of the 26th Annual Conference on Learning Theory , pages =

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source=arxiv_source observed=2026-08-01T19:10:19.611547Z digest=sha256:75dce890fa63a3c1c2e7859e03a559a1b83f6d58cd939cae1af787bd8b233341

Observation 1fa22ec1-7c98-496d-be93-8244026681de · outbound

This paper cites Information-theoretic limits on sparsity recovery in the high-dimensional and noisy setting , Volume =.

Fundamental Limits of Query-Based Subgraph Detection Information-theoretic limits on sparsity recovery in the high-dimensional and noisy setting , Volume =

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source=arxiv_source observed=2026-08-01T19:10:19.714464Z digest=sha256:74f2fc2f7d6599bace4969cb71a6a85a1a5855e8bc5f3c12bff6f139bc14cf8e

Observation 9ab62804-e05d-40d4-b76a-eba650b090a4 · outbound

This paper cites Fourier pca , Year =.

Fundamental Limits of Query-Based Subgraph Detection Fourier pca , Year =

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source=arxiv_source observed=2026-08-01T19:10:19.875464Z digest=sha256:34bf1cb5b8f449579b5e02bb54fc2b7f612dace0bb085006f0a99abba99ea01f

Observation 0c39b92a-fcc8-4576-8ce2-799daef7be6d · outbound

This paper cites Improved approximation of linear threshold functions , Volume =.

Fundamental Limits of Query-Based Subgraph Detection Improved approximation of linear threshold functions , Volume =

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source=arxiv_source observed=2026-08-01T19:10:20.038811Z digest=sha256:9a87210fa649ca4c0b195cd2a6e632266d6f879ebf5aaf30aafff016e20973ea

Observation fce921f1-b64d-4a4b-a120-247ba8ab21f0 · outbound

This paper cites , Date-Added =.

Fundamental Limits of Query-Based Subgraph Detection , Date-Added =

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source=arxiv_source observed=2026-08-01T19:10:20.203379Z digest=sha256:e18e38edf0a61ae3504906f71d531e90abc61f39d520fce3a582c56eca728978

Observation 3eb73ed8-7130-4d80-9a60-ffbeea86065a · outbound

This paper cites CoSaMP: Iterative signal recovery from incomplete and inaccurate samples , Volume =.

Fundamental Limits of Query-Based Subgraph Detection CoSaMP: Iterative signal recovery from incomplete and inaccurate samples , Volume =

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source=arxiv_source observed=2026-08-01T19:10:20.350040Z digest=sha256:e58d4fe77bc609cd45d2522d197fd8b718f175e588fdfb6d8f4a3038b5aa5eaf

Observation bd1674d4-adff-410f-9eb4-77a042493a11 · outbound

This paper cites Subspace pursuit for compressive sensing signal reconstruction , Volume =.

Fundamental Limits of Query-Based Subgraph Detection Subspace pursuit for compressive sensing signal reconstruction , Volume =

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source=arxiv_source observed=2026-08-01T19:10:20.473309Z digest=sha256:45ee7937088bb659ab51922f7374ed6f01c54e70acf9422cba809545c200b50b

Observation e7c122c5-4128-4933-a62a-2d4065c384d0 · outbound

This paper cites Adaptive forward-backward greedy algorithm for learning sparse representations , Volume =.

Fundamental Limits of Query-Based Subgraph Detection Adaptive forward-backward greedy algorithm for learning sparse representations , Volume =

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source=arxiv_source observed=2026-08-01T19:10:20.639385Z digest=sha256:896373339a9036b62c63d0427f45039723efc905351c284b8ddc41e90aa82342

Observation feb9c2e0-0c1e-4332-8b74-a475595259b6 · outbound

This paper cites On the consistency of feature selection using greedy least squares regression , Year =.

Fundamental Limits of Query-Based Subgraph Detection On the consistency of feature selection using greedy least squares regression , Year =

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source=arxiv_source observed=2026-08-01T19:10:20.807728Z digest=sha256:309890688400a35b2e982ff2cb3fc5161b663c5dd19ec3e1e27735e56cc57c0b

Observation 51faaa9a-db57-4a4b-824a-52c2ad9b3be0 · outbound

This paper cites Atomic decomposition by basis pursuit , Volume =.

Fundamental Limits of Query-Based Subgraph Detection Atomic decomposition by basis pursuit , Volume =

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source=arxiv_source observed=2026-08-01T19:10:20.953773Z digest=sha256:91545f9719441820d7b6748b3ddf7d51da82a761187a916821c182d0a17cd99f

Observation 16cfecbb-d6ba-46f3-8815-50c1c118a537 · outbound

This paper cites Greedy approximation , Year =.

Fundamental Limits of Query-Based Subgraph Detection Greedy approximation , Year =

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source=arxiv_source observed=2026-08-01T19:10:21.083020Z digest=sha256:48b9912581511af62be2674aa011427b883baf48c5dddebb6ad4796a6650406c

Observation 2def44a7-d978-4cc1-aa69-e7bca58085d5 · outbound

This paper cites Additive logistic regression: a statistical view of boosting (with discussion and a rejoinder by the authors) , Volume =.

Fundamental Limits of Query-Based Subgraph Detection Additive logistic regression: a statistical view of boosting (with discussion and a rejoinder by the authors) , Volume =

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source=arxiv_source observed=2026-08-01T19:10:21.198257Z digest=sha256:b8203758c2c65a1331ccd0c3593e54e0473fa242782b5e08a63b48cb3811c4d0

Observation 8b9cf60e-a530-41f0-b19b-89c88d87ca71 · outbound

This paper cites High dimensional variable selection , Volume =.

Fundamental Limits of Query-Based Subgraph Detection High dimensional variable selection , Volume =

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source=arxiv_source observed=2026-08-01T19:10:21.302935Z digest=sha256:22c77c8207752e06ffe65893cc1414d59746624dcebdee0db5a0e37c6ef81574

Observation 6fb3af5f-1e32-4775-a62b-0e1705c90c1d · outbound

This paper cites , Date-Added =.

Fundamental Limits of Query-Based Subgraph Detection , Date-Added =

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source=arxiv_source observed=2026-08-01T19:10:21.402617Z digest=sha256:a5d7147fe9cf65d19d7e702be252fe762c4360df06c61ee2747196988936b9d3

Observation 9f5fda40-76fd-4fe9-b441-ab994205e7db · outbound

This paper cites and Banavar, J.

Fundamental Limits of Query-Based Subgraph Detection and Banavar, J

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source=arxiv_source observed=2026-08-01T19:10:21.518397Z digest=sha256:7632a73224d2ecc10ed7da962e1b060e08800e242fcb753a618671d9605b7eeb

Observation b7edba93-7a1e-4652-b66f-29453296c3ec · outbound

This paper cites and Ollion, C.

Fundamental Limits of Query-Based Subgraph Detection and Ollion, C

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source=arxiv_source observed=2026-08-01T19:10:21.588019Z digest=sha256:9f66c55f7af39fe61537c2bd5b65a18f2664316c6a6a1e7f2b5d07e8d21841cd

Observation 2ab686d0-7559-4240-a416-02dacc406433 · outbound

This paper cites Constraint satisfaction problems and neural networks: A statistical physics perspective , Volume =.

Fundamental Limits of Query-Based Subgraph Detection Constraint satisfaction problems and neural networks: A statistical physics perspective , Volume =

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source=arxiv_source observed=2026-08-01T19:10:21.708383Z digest=sha256:65c50a1f9eb5b5af415d8a4295b78e83ae767a7ce1725d48bb19c0fe99428712

Observation 02302c3f-cc11-4e8b-996a-79e53ab84273 · outbound

This paper cites , Date-Added =.

Fundamental Limits of Query-Based Subgraph Detection , Date-Added =

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source=arxiv_source observed=2026-08-01T19:10:21.820180Z digest=sha256:3214705af4f67bc2b0f12268567c433a66aebf502fc60fdb5618bfa6fbd93065

Observation c3477298-23fd-4650-8cc6-134a4131912b · outbound

This paper cites and Sejnowski, T.

Fundamental Limits of Query-Based Subgraph Detection and Sejnowski, T

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source=arxiv_source observed=2026-08-01T19:10:21.938157Z digest=sha256:500bc897d06860f6041a1f2d4a2faab1f385a6d79da276959abb2a0b46e2a6e2

Observation 581b8ede-4c3d-491d-9417-236820647e8d · outbound

This paper cites and Hinton, G.

Fundamental Limits of Query-Based Subgraph Detection and Hinton, G

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Observation e745db1c-26bd-4e21-8336-8f7d35f59676 · outbound

This paper cites Evolutionary information for specifying a protein fold , Volume =.

Fundamental Limits of Query-Based Subgraph Detection Evolutionary information for specifying a protein fold , Volume =

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Observation 040bb45b-b385-410b-947d-6881dd3eaafc · outbound

This paper cites and Monasson, R.

Fundamental Limits of Query-Based Subgraph Detection and Monasson, R

Reference 82

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Observation f4cd8b7c-a2d3-484f-bc92-7feef43cee14 · outbound

This paper cites and Walczak, A.

Fundamental Limits of Query-Based Subgraph Detection and Walczak, A

Reference 83

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source=arxiv_source observed=2026-08-01T19:10:22.363977Z digest=sha256:a892213541305569dbda0df55c39fffbdc1c876a585d200334197033fc21a68c

Observation 55bfcbe0-ba49-4d56-8944-da805528db4f · outbound

This paper cites and Aurell, E.

Fundamental Limits of Query-Based Subgraph Detection and Aurell, E

Reference 84

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source=arxiv_source observed=2026-08-01T19:10:22.514566Z digest=sha256:e8812979d9f89a71646397c0761baa7f8910dff07c58dd72f38ca03010f96aeb

Observation 179b93c6-d53a-4aa5-9bbb-3dc8fbffba72 · outbound

This paper cites and Ricci-Tersenghi, F.

Fundamental Limits of Query-Based Subgraph Detection and Ricci-Tersenghi, F

Reference 85

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source=arxiv_source observed=2026-08-01T19:10:22.605359Z digest=sha256:41d082f716f81b221c96201530fe1f1254cd6a71083c32530c321cd7ba578767

Observation 1e659a70-ca49-4646-bc7c-6e2cc40a6b79 · outbound

This paper cites Advanced mean field methods: Theory and practice , Year =.

Fundamental Limits of Query-Based Subgraph Detection Advanced mean field methods: Theory and practice , Year =

Reference 86

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source=arxiv_source observed=2026-08-01T19:10:22.710044Z digest=sha256:cb9b88ba82eca12553199d7323510845325dfb445d4ef5071759ae553e048d59

Observation e2b18e30-e515-46d4-b995-7e24c02d2033 · outbound

This paper cites and White, R.

Fundamental Limits of Query-Based Subgraph Detection and White, R

Reference 87

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source=arxiv_source observed=2026-08-01T19:10:22.811530Z digest=sha256:f691dab4be2c2a5ee1a47e75ad00657b5da3bd503b6417ff65271a691561de6c

Observation 033597d4-6b3e-4f16-a2f3-c1aa41562b88 · outbound

This paper cites and Leibler, S.

Fundamental Limits of Query-Based Subgraph Detection and Leibler, S

Reference 88

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source=arxiv_source observed=2026-08-01T19:10:22.883893Z digest=sha256:09c875af0940e5b264c256ae46a94a4fae71a7cf03a35f2a44958bfa9f649298

Observation 0514ba0a-12d7-4b53-a37b-7f5666ffff77 · outbound

This paper cites and Berry, M.

Fundamental Limits of Query-Based Subgraph Detection and Berry, M

Reference 89

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source=arxiv_source observed=2026-08-01T19:10:22.953287Z digest=sha256:d5c8fcb68cfdc000722fcaea904327e8421fe56c5dfb7d2e93dabd39e82bae16

Observation 27e6ed50-f76e-4151-a8fa-56c2db0d9417 · outbound

This paper cites and Samorodnitsky, A.

Fundamental Limits of Query-Based Subgraph Detection and Samorodnitsky, A

Reference 90

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source=arxiv_source observed=2026-08-01T19:10:23.029656Z digest=sha256:f9abd4b10596867b4fcd51d8f2c30d0a747220936f98ee1edaf9a84ba4671599

Observation 64a3be8d-56d5-4923-979a-90e62cbda32d · outbound

This paper cites , Date-Added =.

Fundamental Limits of Query-Based Subgraph Detection , Date-Added =

Reference 91

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source=arxiv_source observed=2026-08-01T19:10:23.108498Z digest=sha256:a9e0ba51b55ada55dd010be3fc398b092576235885aac42c9c2e195feb4aa16c

Observation 35a55940-8228-44ff-8891-5049d006a46b · outbound

This paper cites , Date-Added =.

Fundamental Limits of Query-Based Subgraph Detection , Date-Added =

Reference 92

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source=arxiv_source observed=2026-08-01T19:10:23.171130Z digest=sha256:1f1d6ebf19ab696ee938cb0b795c5096f0d0f0ef0c93e131da29b79422674e57

Observation 5d028a87-2ee0-4895-9554-86d4e7870418 · outbound

This paper cites , Date-Added =.

Fundamental Limits of Query-Based Subgraph Detection , Date-Added =

Reference 93

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source=arxiv_source observed=2026-08-01T19:10:23.280961Z digest=sha256:7f29c88ff855fef4a26d0f5207979605993f1cbe2343a8dd60c54c168b3ca15b

Observation 2e669179-e0ad-436f-88f8-f9d1be10e201 · outbound

This paper cites , Booktitle =.

Fundamental Limits of Query-Based Subgraph Detection , Booktitle =

Reference 94

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source=arxiv_source observed=2026-08-01T19:10:23.362909Z digest=sha256:16b6008ecfa92d79e7f9c218c70da77c933f404c3a6e75d259d9426b0c6ae5b2

Observation 3322d0a0-dae5-494b-a24e-c9a0241f617a · outbound

This paper cites and Srikant, R.

Fundamental Limits of Query-Based Subgraph Detection and Srikant, R

Reference 95

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source=arxiv_source observed=2026-08-01T19:10:23.457319Z digest=sha256:9553fa7beecc343be50f9956e459d1368dbbbc3d5de4ea6c49c335174995a3a6

Observation c4722e0f-969b-4877-a8a4-2c5c5b7d9a4a · outbound

This paper cites and Wainwright, M.

Fundamental Limits of Query-Based Subgraph Detection and Wainwright, M

Reference 96

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source=arxiv_source observed=2026-08-01T19:10:23.519631Z digest=sha256:5d623ce2434d2c64f9e38b313fb3cacce0f402366e52f0040a362f8b06e77c20

Observation 65102260-ae06-4e99-9ff8-9897f7868765 · outbound

This paper cites and Ravikumar, P.

Fundamental Limits of Query-Based Subgraph Detection and Ravikumar, P

Reference 97

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source=arxiv_source observed=2026-08-01T19:10:23.600896Z digest=sha256:3d28ac9a41184a78048563000c3cc7d539c842893dc40d33ffefb0cea184c7f8

Observation e361655c-0758-4ba6-88bf-12c90a724c91 · outbound

This paper cites and B\"uhlmann, P.

Fundamental Limits of Query-Based Subgraph Detection and B\"uhlmann, P

Reference 98

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source=arxiv_source observed=2026-08-01T19:10:23.748428Z digest=sha256:2a983d49167e698004e73e7e43c32e044d9f324882a0b5ded5eeeadb53a53454

Observation 0e9c50c0-b10f-441c-88c1-0d90e1d801ab · outbound

This paper cites , Date-Added =.

Fundamental Limits of Query-Based Subgraph Detection , Date-Added =

Reference 99

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source=arxiv_source observed=2026-08-01T19:10:23.831195Z digest=sha256:b62fcf53a7fc00d920a7b5c32023b3a11d9072c5b68af59c2d4cca08bac57aee

Observation 13814b54-1552-4b23-8bf7-3a3da28e54e3 · outbound

This paper cites and Jerrum, M.

Fundamental Limits of Query-Based Subgraph Detection and Jerrum, M

Reference 100

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source=arxiv_source observed=2026-08-01T19:10:23.858378Z digest=sha256:59bb424207fa1ac62d4c2f1f3bdb0d7670f1d62b724fd171787d65af85943778

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