Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-03T12:17:34.505819Z
Paper Citation Record · LEDGER
As of 23 August 2026, this Paper Citation Record lists 49 of 49 outbound references and 0 inbound Pith citation observations for arXiv:2601.03946.
A citation records a reference. It does not transfer a finding from one paper to another.
Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-03T12:17:34.505819Z
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-22T06:32:14.747728+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links
A source-named dated measurement, never combined with another source.
Source: cited_works
49 of 49 outbound references displayed
External citation measurements
No source-named external measurement is stored.
Observation 97d62e9c-857b-4d0d-9d7b-fefa069b234a · outbound
Provably Finding a Hidden Dense Submatrix among Many Planted Dense Submatrices via Convex Programming [Accessed 24- 10-2025]
Reference 1
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Observation 8e533efe-e76c-430e-a43e-143d7c80b618 · outbound
Provably Finding a Hidden Dense Submatrix among Many Planted Dense Submatrices via Convex Programming Community detection and stochastic block models, 2023
Reference 2
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Observation 0466d591-722d-4d79-8c7c-2580b05bff75 · outbound
Provably Finding a Hidden Dense Submatrix among Many Planted Dense Submatrices via Convex Programming Inapprox- imability of densestκ-subgraph from average case hardness.Unpublished manuscript, 1:6, 2011
Reference 3
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Observation 52f58c51-b784-4168-a561-1ce0a86d873e · outbound
Provably Finding a Hidden Dense Submatrix among Many Planted Dense Submatrices via Convex Programming Finding a large hidden clique in a random graph.Random Structures & Algorithms, 13(3-4):457–466, 1998
Reference 4
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Observation de5b8040-58e7-4b1a-b2bf-9e7619a2774f · outbound
Provably Finding a Hidden Dense Submatrix among Many Planted Dense Submatrices via Convex Programming Guaranteed clustering and biclustering via semidefinite programming.Mathe- matical Programming, 147(1):429–465, 2014
Reference 5
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Observation bd28b4c2-5933-40a9-a05d-17538c243727 · outbound
Provably Finding a Hidden Dense Submatrix among Many Planted Dense Submatrices via Convex Programming Guaranteed recovery of planted cliques and dense subgraphs by convex relax- ation.Journal of Optimization Theory and Applications, 167(2):653–675, 2015
Reference 6
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Observation 53bf2ce0-891d-4d0d-82eb-7cd163379dfb · outbound
Provably Finding a Hidden Dense Submatrix among Many Planted Dense Submatrices via Convex Programming Nuclear norm minimization for the planted clique and biclique problems.Mathematical programming, 129(1):69–89, 2011
Reference 7
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Observation e2f7cb87-e1aa-4fed-831b-8d4103b77500 · outbound
Provably Finding a Hidden Dense Submatrix among Many Planted Dense Submatrices via Convex Programming Finding large and small dense subgraphs
Reference 8
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Observation 947defea-54bd-47a2-842e-548c7563bf94 · outbound
Provably Finding a Hidden Dense Submatrix among Many Planted Dense Submatrices via Convex Programming Clique relaxations in social network analysis: The maximum k-plex problem.Operations Research, 59(1):133–142, 2011
Reference 9
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Observation 2f04e528-84a9-4531-915c-d4bfb76eea74 · outbound
Provably Finding a Hidden Dense Submatrix among Many Planted Dense Submatrices via Convex Programming Sharp nonasymptotic bounds on the norm of random matrices with independent entries
Reference 10
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Observation 44ef71d0-9906-44af-a539-7488098557cd · outbound
Provably Finding a Hidden Dense Submatrix among Many Planted Dense Submatrices via Convex Programming The game of Game of Thrones: Networked concordances and fractal dramaturgy
Reference 11
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Observation 845471cc-edf7-476b-a40d-4c40578b8f9d · outbound
Provably Finding a Hidden Dense Submatrix among Many Planted Dense Submatrices via Convex Programming Network of Thrones.Math Horizons, 23(4):18–22, 2016
Reference 12
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Observation 45c9c65a-4279-4ba8-a2a7-948ae42410be · outbound
Provably Finding a Hidden Dense Submatrix among Many Planted Dense Submatrices via Convex Programming Mining market data: A network ap- proach.Computers & Operations Research, 33(11):3171–3184, 2006
Reference 13
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Observation af8d2369-273b-4424-aae8-48db79525495 · outbound
Provably Finding a Hidden Dense Submatrix among Many Planted Dense Submatrices via Convex Programming Convex optimization for the densest subgraph and densest submatrix problems
Reference 14
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Observation d1bdd4f7-3e18-4454-b60c-71a3f0b57f63 · outbound
Provably Finding a Hidden Dense Submatrix among Many Planted Dense Submatrices via Convex Programming Oxford university press, 2013
Reference 15
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Observation cc004b90-0eb1-430a-aa94-6593d72fbea7 · outbound
Provably Finding a Hidden Dense Submatrix among Many Planted Dense Submatrices via Convex Programming Convex pptimization.Cambridge UP, 2004
Reference 16
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Observation 5da91404-4c81-41c2-a1cd-150ed7fec67e · outbound
Provably Finding a Hidden Dense Submatrix among Many Planted Dense Submatrices via Convex Programming Distributed opti- mization and statistical learning via the alternating direction method of multipliers.Foundations and Trends®in Machine learning, 3(1):1–122, 2011
Reference 17
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Observation 49b3497b-e9cb-4676-b581-b15d593335f5 · outbound
Provably Finding a Hidden Dense Submatrix among Many Planted Dense Submatrices via Convex Programming Algorithm 457: finding all cliques of an undirected graph.Commu- nications of the ACM, 16(9):575–577, 1973
Reference 18
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Observation 8d85e0cb-54b9-4499-8db9-406b2f539594 · outbound
Provably Finding a Hidden Dense Submatrix among Many Planted Dense Submatrices via Convex Programming Robust principal component analysis? Journal of the ACM (JACM), 58(3):1–37, 2011
Reference 19
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Observation 0a0142c5-994b-4f01-af90-11c3e0007037 · outbound
Provably Finding a Hidden Dense Submatrix among Many Planted Dense Submatrices via Convex Programming A note on the problem of reporting maximal cliques
Reference 20
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Observation 0d9179aa-1f70-44db-b6dc-6f384aeb56cb · outbound
Provably Finding a Hidden Dense Submatrix among Many Planted Dense Submatrices via Convex Programming Rank-sparsity incoherence for matrix decomposition.SIAM Journal on Optimization, 21(2):572–596, 2011
Reference 21
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Observation 7bcf85d2-7d14-4168-a3a9-0e49326e6560 · outbound
Provably Finding a Hidden Dense Submatrix among Many Planted Dense Submatrices via Convex Programming Statistical-computational phase transitions in planted models: The high-dimensional setting
Reference 22
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Observation 0b59559f-bfa5-4c64-8403-d2e3d4b42156 · outbound
Provably Finding a Hidden Dense Submatrix among Many Planted Dense Submatrices via Convex Programming Detection and recovery of hidden submatrices
Reference 23
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Observation 675beec8-cf21-401e-9370-d56afb912cdc · outbound
Provably Finding a Hidden Dense Submatrix among Many Planted Dense Submatrices via Convex Programming A generalization of the Sherman-Morrison-Woodbury formula.Applied Mathe- matics Letters, 24(9):1561–1564, 2011
Reference 24
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Observation 860af8eb-7f56-4927-aafd-a31ea50e3821 · outbound
Provably Finding a Hidden Dense Submatrix among Many Planted Dense Submatrices via Convex Programming Finding approximately rank-one submatrices with the nuclear norm andℓ 1-norm.SIAM Journal on Optimization, 23(4):2502–2540, 2013
Reference 25
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Observation cdf4ff55-ee7c-4ffb-b620-774ee064e5de · outbound
Provably Finding a Hidden Dense Submatrix among Many Planted Dense Submatrices via Convex Programming Relations between average case complexity and approximation complexity
Reference 26
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Observation 53edb7ee-224a-495c-9f99-85e129c76177 · outbound
Provably Finding a Hidden Dense Submatrix among Many Planted Dense Submatrices via Convex Programming Finding and certifying a large hidden clique in a semirandom graph.Random Structures & Algorithms, 16(2):195–208, 2000
Reference 27
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Observation 0affa2c1-9ebf-4310-8bba-5e4817775888 · outbound
Provably Finding a Hidden Dense Submatrix among Many Planted Dense Submatrices via Convex Programming Community structure in jazz.Advances in complex systems, 6(04):565–573, 2003
Reference 28
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Observation 2cd986bf-e574-4b8c-875a-98f97c427997 · outbound
Provably Finding a Hidden Dense Submatrix among Many Planted Dense Submatrices via Convex Programming JHU Press, 2013
Reference 29
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Observation ebaedd7d-9e5c-40a0-87ec-e4014e96db2b · outbound
Provably Finding a Hidden Dense Submatrix among Many Planted Dense Submatrices via Convex Programming Identification of a 5-protein biomarker molecular signa- ture for predicting Alzheimer’s disease.PloS One, 3(9):e3111, 2008
Reference 30
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Observation a4b0c7c4-374e-4112-97e9-bfa3f5232ce0 · outbound
Provably Finding a Hidden Dense Submatrix among Many Planted Dense Submatrices via Convex Programming On the linear convergence of the alternating direction method of multipliers.Mathematical Programming, 162(1):165–199, 2017
Reference 31
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Observation 9c2d6ed3-0cc9-47f6-8d49-7cb1c18e8d3e · outbound
Provably Finding a Hidden Dense Submatrix among Many Planted Dense Submatrices via Convex Programming Impact of interference on multi-hop wireless network performance
Reference 32
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Observation 956cfcb3-ca91-4c3f-a3eb-6565684419a3 · outbound
Provably Finding a Hidden Dense Submatrix among Many Planted Dense Submatrices via Convex Programming Reducibility among combinatorial problems
Reference 33
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Observation 99b8ee45-103a-492e-baef-051e3ad2081f · outbound
Provably Finding a Hidden Dense Submatrix among Many Planted Dense Submatrices via Convex Programming Ruling out PTAs for graph min-bisection, densek-subgraph, and bipartite clique
Reference 34
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Observation 8c6749c1-5d4a-46a1-a9ec-97fb1925b151 · outbound
Provably Finding a Hidden Dense Submatrix among Many Planted Dense Submatrices via Convex Programming AcM Press New York, 1993
Reference 35
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Observation b6ea1551-1d15-4b08-952c-9948b7a41c15 · outbound
Provably Finding a Hidden Dense Submatrix among Many Planted Dense Submatrices via Convex Programming A survey on the densest subgraph problem and its variants.ACM Computing Surveys, 56(8):1–40, 2024
Reference 36
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Observation b7940e20-8cc7-4978-bd8f-6beda1ad99ee · outbound
Provably Finding a Hidden Dense Submatrix among Many Planted Dense Submatrices via Convex Programming The dimension-free structure of nonhomoge- neous random matrices.Inventiones mathematicae, 214(3):1031–1080, 2018
Reference 37
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Observation ccd8a6c3-9694-4396-b91b-7b090f998d7f · outbound
Provably Finding a Hidden Dense Submatrix among Many Planted Dense Submatrices via Convex Programming Unresolved cited work
Reference 38
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Observation cb4b82d6-e2b9-4832-a920-0e6c7984fe1d · outbound
Provably Finding a Hidden Dense Submatrix among Many Planted Dense Submatrices via Convex Programming Maximum cliques in protein structure comparison
Reference 39
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Observation d937ad82-e16e-48db-8e42-760336b93b8a · outbound
Provably Finding a Hidden Dense Submatrix among Many Planted Dense Submatrices via Convex Programming Harnessing the mathematics of matrix decomposition to solve planted and maximum clique problem
Reference 40
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Observation 4106c591-8273-4da3-8fcb-9e98204b9ebe · outbound
Provably Finding a Hidden Dense Submatrix among Many Planted Dense Submatrices via Convex Programming Maximum edge bi-clique via matrix decomposition.Journal of Industrial and Management Optimization, 21(11):6270–6294, 2025
Reference 41
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Observation 8c1ae675-89c2-495b-a64e-865c2fc10956 · outbound
Provably Finding a Hidden Dense Submatrix among Many Planted Dense Submatrices via Convex Programming Clique relaxation models in social network analysis
Reference 42
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Observation cb7639a4-e8c0-46fc-8c47-05476a618acd · outbound
Provably Finding a Hidden Dense Submatrix among Many Planted Dense Submatrices via Convex Programming Guaranteed minimum-rank solutions of linear matrix equations via nuclear norm minimization.SIAM review, 52(3):471–501, 2010
Reference 43
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Observation 2d68486e-9985-48ac-bf7b-b531139db097 · outbound
Provably Finding a Hidden Dense Submatrix among Many Planted Dense Submatrices via Convex Programming Graph clustering.Computer Science Review, 1(1):27–64, 2007
Reference 44
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Observation faddf3c8-a582-491a-b6dc-e69be63f2e06 · outbound
Provably Finding a Hidden Dense Submatrix among Many Planted Dense Submatrices via Convex Programming Sharp phase transitions in estimation with low-degree polynomials
Reference 45
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Observation 2700c4e6-6ceb-46de-8568-cfaf2a8de252 · outbound
Provably Finding a Hidden Dense Submatrix among Many Planted Dense Submatrices via Convex Programming A semidefinite programming-based branch-and-cut algorithm for biclustering
Reference 46
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Observation 5b472798-e795-4a55-a8d6-aaa6b42ebca4 · outbound
Provably Finding a Hidden Dense Submatrix among Many Planted Dense Submatrices via Convex Programming The worst-case time complexity for generat- ing all maximal cliques and computational experiments.Theoretical computer science, 363(1):28–42, 2006
Reference 47
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Observation 6fbbb634-cd91-4b99-a018-d8cc66d9ffeb · outbound
Provably Finding a Hidden Dense Submatrix among Many Planted Dense Submatrices via Convex Programming User-friendly tail bounds for sums of random matrices.Foundations of computational mathematics, 12:389–434, 2012
Reference 48
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Observation 01e5a685-9e9e-41b3-86fb-890c8a5d4286 · outbound
Provably Finding a Hidden Dense Submatrix among Many Planted Dense Submatrices via Convex Programming An information flow model for conflict and fission in small groups.Journal of anthropological research, 33(4):452–473, 1977
Reference 49
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No inbound Pith citation observations are available.