Efficient Learning of Balanced Signed Graphs via Sparse Linear Programming | Paper Citation Record

Observation 1e236dc3-cc14-4a17-b12d-7d90e6bf816e · outbound

This paper cites The emerging field of signal processing on graphs: Extending high- dimensional data analysis to networks and other irregular domains,.

Efficient Learning of Balanced Signed Graphs via Sparse Linear Programming The emerging field of signal processing on graphs: Extending high- dimensional data analysis to networks and other irregular domains,

Reference 1

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Observation 65cc0d6a-9742-494c-9748-eb5c04a42be5 · outbound

This paper cites Graph Signal Processing: Overview, Challenges, and Applications,.

Efficient Learning of Balanced Signed Graphs via Sparse Linear Programming Graph Signal Processing: Overview, Challenges, and Applications,

Reference 2

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Observation ae00e582-f289-40fe-bec9-4f4c87c829b1 · outbound

This paper cites Sampling Signals on Graphs: From Theory to Applications,.

Efficient Learning of Balanced Signed Graphs via Sparse Linear Programming Sampling Signals on Graphs: From Theory to Applications,

Reference 3

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This paper cites Semi-supervised classification with graph convolutional networks,.

Efficient Learning of Balanced Signed Graphs via Sparse Linear Programming Semi-supervised classification with graph convolutional networks,

Reference 4

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This paper cites Sparse inverse covariance estimation with the graphical lasso,.

Efficient Learning of Balanced Signed Graphs via Sparse Linear Programming Sparse inverse covariance estimation with the graphical lasso,

Reference 5

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This paper cites How to Learn a Graph from Smooth Signals,.

Efficient Learning of Balanced Signed Graphs via Sparse Linear Programming How to Learn a Graph from Smooth Signals,

Reference 6

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This paper cites Learning heat diffusion graphs,.

Efficient Learning of Balanced Signed Graphs via Sparse Linear Programming Learning heat diffusion graphs,

Reference 7

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Observation b49ca4fe-8736-4b34-9fa6-bc127d4f3886 · outbound

This paper cites Graph Signal Denoising via Trilateral Filter on Graph Spectral Domain,.

Efficient Learning of Balanced Signed Graphs via Sparse Linear Programming Graph Signal Denoising via Trilateral Filter on Graph Spectral Domain,

Reference 8

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Observation 2c9a7b38-b676-45da-9769-1ae90046546c · outbound

This paper cites Graph Laplacian regularization for inverse imaging: Analysis in the continuous domain,.

Efficient Learning of Balanced Signed Graphs via Sparse Linear Programming Graph Laplacian regularization for inverse imaging: Analysis in the continuous domain,

Reference 9

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This paper cites Localized spectral graph filter frames: A unifying framework, survey of design considerations, and numerical comparison,.

Efficient Learning of Balanced Signed Graphs via Sparse Linear Programming Localized spectral graph filter frames: A unifying framework, survey of design considerations, and numerical comparison,

Reference 10

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This paper cites Wavelets on graphs via spectral graph theory,.

Efficient Learning of Balanced Signed Graphs via Sparse Linear Programming Wavelets on graphs via spectral graph theory,

Reference 11

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This paper cites Bilateral filter: Graph spectral interpretation and extensions,.

Efficient Learning of Balanced Signed Graphs via Sparse Linear Programming Bilateral filter: Graph spectral interpretation and extensions,

Reference 12

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Observation 91f3faa5-b6a7-45e9-b1be-a5dc0049e796 · outbound

This paper cites Signal recovery on graphs: Variation minimization,.

Efficient Learning of Balanced Signed Graphs via Sparse Linear Programming Signal recovery on graphs: Variation minimization,

Reference 13

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This paper cites Graph-based joint dequantization and contrast enhancement of poorly lit jpeg images,.

Efficient Learning of Balanced Signed Graphs via Sparse Linear Programming Graph-based joint dequantization and contrast enhancement of poorly lit jpeg images,

Reference 14

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Observation 7f079f54-3ffc-42cc-b489-a7ae74d1d2c8 · outbound

This paper cites Interpolation and denoising of graph signals using plug-and-play admm,.

Efficient Learning of Balanced Signed Graphs via Sparse Linear Programming Interpolation and denoising of graph signals using plug-and-play admm,

Reference 15

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This paper cites Graph signal restoration using nested deep algorithm unrolling,.

Efficient Learning of Balanced Signed Graphs via Sparse Linear Programming Graph signal restoration using nested deep algorithm unrolling,

Reference 16

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Observation b2f48b8d-91f8-4600-ba85-69cfb4c1de93 · outbound

This paper cites On the Laplacian Eigenvalues of Signed Graphs,.

Efficient Learning of Balanced Signed Graphs via Sparse Linear Programming On the Laplacian Eigenvalues of Signed Graphs,

Reference 17

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Observation ddae6656-2b26-470b-b0eb-2a5209051b09 · outbound

This paper cites Spectral Analysis of k- Balanced Signed Graphs,.

Efficient Learning of Balanced Signed Graphs via Sparse Linear Programming Spectral Analysis of k- Balanced Signed Graphs,

Reference 18

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Observation 22c49c01-ee2b-4ec3-9af9-e1cf490e071d · outbound

This paper cites Spectral Analysis of Signed Graphs for Clustering, Prediction and Visualization,.

Efficient Learning of Balanced Signed Graphs via Sparse Linear Programming Spectral Analysis of Signed Graphs for Clustering, Prediction and Visualization,

Reference 19

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Observation 4f4a0951-111b-4d25-b082-0c09367ede46 · outbound

This paper cites Signal Processing on Signed Graphs: Funda- mentals and Potentials,.

Efficient Learning of Balanced Signed Graphs via Sparse Linear Programming Signal Processing on Signed Graphs: Funda- mentals and Potentials,

Reference 20

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This paper cites Discrete nodal domain theorems,.

Efficient Learning of Balanced Signed Graphs via Sparse Linear Programming Discrete nodal domain theorems,

Reference 21

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Observation f8492111-9da9-4291-90b0-4a91c088418d · outbound

This paper cites Efficient signed graph sampling via balancing & gershgorin disc perfect alignment,.

Efficient Learning of Balanced Signed Graphs via Sparse Linear Programming Efficient signed graph sampling via balancing & gershgorin disc perfect alignment,

Reference 22

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This paper cites Efficient learning of balanced signature graphs,.

Efficient Learning of Balanced Signed Graphs via Sparse Linear Programming Efficient learning of balanced signature graphs,

Reference 23

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Observation ca202b35-efff-4dc5-b3be-7db2a0cab632 · outbound

This paper cites The graphical lasso: New insights and alternatives,.

Efficient Learning of Balanced Signed Graphs via Sparse Linear Programming The graphical lasso: New insights and alternatives,

Reference 24

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Observation 77f17615-339f-4ab2-87b3-ce878eca94f9 · outbound

This paper cites Balancing signed graphs,.

Efficient Learning of Balanced Signed Graphs via Sparse Linear Programming Balancing signed graphs,

Reference 25

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Observation 2ac33abc-8208-4be7-b80f-ba8ed263ebc1 · outbound

This paper cites Linear-Time Sampling on Signed Graphs Via Gershgorin Disc Perfect Alignment,.

Efficient Learning of Balanced Signed Graphs via Sparse Linear Programming Linear-Time Sampling on Signed Graphs Via Gershgorin Disc Perfect Alignment,

Reference 26

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Observation 48039b14-592e-4961-bf07-4edafc902c9b · outbound

This paper cites Signed graph balancing with graph cut,.

Efficient Learning of Balanced Signed Graphs via Sparse Linear Programming Signed graph balancing with graph cut,

Reference 27

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This paper cites A constrained ℓ1 minimization approach to sparse precision matrix estimation,.

Efficient Learning of Balanced Signed Graphs via Sparse Linear Programming A constrained ℓ1 minimization approach to sparse precision matrix estimation,

Reference 28

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Observation f1765fb5-aaca-463d-b8f4-d54d84344feb · outbound

This paper cites On the notion of balance of a signed graph.

Efficient Learning of Balanced Signed Graphs via Sparse Linear Programming On the notion of balance of a signed graph

Reference 29

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This paper cites A new alternating direction method for linear programming,.

Efficient Learning of Balanced Signed Graphs via Sparse Linear Programming A new alternating direction method for linear programming,

Reference 30

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This paper cites The determination of the order of an autoregression,.

Efficient Learning of Balanced Signed Graphs via Sparse Linear Programming The determination of the order of an autoregression,

Reference 31

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Observation 744a42c4-6b0b-4353-8bef-be1434c9bb97 · outbound

This paper cites Variational Splines and Paley–Wiener Spaces on Combina- torial Graphs,.

Efficient Learning of Balanced Signed Graphs via Sparse Linear Programming Variational Splines and Paley–Wiener Spaces on Combina- torial Graphs,

Reference 32

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This paper cites Graph attention networks,.

Efficient Learning of Balanced Signed Graphs via Sparse Linear Programming Graph attention networks,

Reference 33

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Observation 6bab92ca-478a-4791-b6d1-d475b2b4870c · outbound

This paper cites Graph Learning From Data Under Laplacian and Structural Constraints,.

Efficient Learning of Balanced Signed Graphs via Sparse Linear Programming Graph Learning From Data Under Laplacian and Structural Constraints,

Reference 34

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Observation dd6d0f03-ab56-4e4f-9c6d-0ef7e49cca21 · outbound

This paper cites Kumar, J.

Efficient Learning of Balanced Signed Graphs via Sparse Linear Programming Kumar, J

Reference 35

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This paper cites Spectral graph learning with core eigenvectors prior via iterative GLASSO and projection,.

Efficient Learning of Balanced Signed Graphs via Sparse Linear Programming Spectral graph learning with core eigenvectors prior via iterative GLASSO and projection,

Reference 36

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Observation a3b5281c-6a9b-43f5-b9fb-5666101035b6 · outbound

This paper cites Learning lapla- cian matrix in smooth graph signal representations,.

Efficient Learning of Balanced Signed Graphs via Sparse Linear Programming Learning lapla- cian matrix in smooth graph signal representations,

Reference 37

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Observation 45259283-5a8f-491b-a07f-80f67825fadf · outbound

This paper cites Learning graphs from data: A signal representation perspective,.

Efficient Learning of Balanced Signed Graphs via Sparse Linear Programming Learning graphs from data: A signal representation perspective,

Reference 38

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This paper cites Joint signal interpolation / time-varying graph estimation via smoothness and low-rank priors,.

Efficient Learning of Balanced Signed Graphs via Sparse Linear Programming Joint signal interpolation / time-varying graph estimation via smoothness and low-rank priors,

Reference 39

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Observation 0837887b-b81a-4136-b6a5-6430f1f0dccd · outbound

This paper cites Feature graph learning for 3d point cloud denoising,.

Efficient Learning of Balanced Signed Graphs via Sparse Linear Programming Feature graph learning for 3d point cloud denoising,

Reference 40

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Observation 1f468e9e-abaa-4f76-82c2-36015654400d · outbound

This paper cites Signed Graph Metric Learning via Gershgorin Disc Perfect Alignment,.

Efficient Learning of Balanced Signed Graphs via Sparse Linear Programming Signed Graph Metric Learning via Gershgorin Disc Perfect Alignment,

Reference 41

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Observation dfbdab8c-3de8-4372-a8bc-1b57e1bcac87 · outbound

This paper cites Interpretable lightweight transformer via unrolling of learned graph smoothness priors,.

Efficient Learning of Balanced Signed Graphs via Sparse Linear Programming Interpretable lightweight transformer via unrolling of learned graph smoothness priors,

Reference 42

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Observation b0e96916-f2a1-465a-9d24-463f3be8105a · outbound

This paper cites Bilateral filtering for gray and color images,.

Efficient Learning of Balanced Signed Graphs via Sparse Linear Programming Bilateral filtering for gray and color images,

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:44:16.771088Z

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Observation f69854da-42ea-4434-9871-ea4b1505db3a · outbound

This paper cites Spectral analysis of signed graphs for clustering, prediction and visualization,.

Efficient Learning of Balanced Signed Graphs via Sparse Linear Programming Spectral analysis of signed graphs for clustering, prediction and visualization,

Reference 44

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This paper cites Efficient learning of balanced signed graphs via iterative linear programming,.

Efficient Learning of Balanced Signed Graphs via Sparse Linear Programming Efficient learning of balanced signed graphs via iterative linear programming,

Reference 45

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:44:16.740790Z

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Observation 2b0740f0-8a93-4070-9de5-a7518b6801a4 · outbound

This paper cites A faster algorithm for solving general LPs,.

Efficient Learning of Balanced Signed Graphs via Sparse Linear Programming A faster algorithm for solving general LPs,

Reference 46

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:44:16.708958Z

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Observation d39ca012-9299-4af4-a311-20fb69d99801 · outbound

This paper cites Graph Fourier transform with negative edges for depth image coding,.

Efficient Learning of Balanced Signed Graphs via Sparse Linear Programming Graph Fourier transform with negative edges for depth image coding,

Reference 47

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:44:16.671139Z

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Observation dfa3b4ef-1dcc-418a-8a74-f18546fb9192 · outbound

This paper cites an unresolved cited work.

Efficient Learning of Balanced Signed Graphs via Sparse Linear Programming Unresolved cited work

Reference 48

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Observation 468c3c18-b8ff-4fe3-a33d-ac0a0df9ea7d · outbound

This paper cites Graph spectral image processing,.

Efficient Learning of Balanced Signed Graphs via Sparse Linear Programming Graph spectral image processing,

Reference 49

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:44:16.589542Z

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Observation a21b514f-8047-4132-9e10-3114f5306466 · outbound

This paper cites Complex graph Lapla- cian regularizer for inferencing grid states,.

Efficient Learning of Balanced Signed Graphs via Sparse Linear Programming Complex graph Lapla- cian regularizer for inferencing grid states,

Reference 50

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:44:16.548704Z

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Observation ad9b0360-8069-45d1-8b06-9c40aaef73c1 · outbound

This paper cites Semidefinite relaxation of quadratic optimization problems,.

Efficient Learning of Balanced Signed Graphs via Sparse Linear Programming Semidefinite relaxation of quadratic optimization problems,

Reference 51

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Observation 58bb3205-245c-480f-8605-11332383d624 · outbound

This paper cites Dynamics of social balance on networks,.

Efficient Learning of Balanced Signed Graphs via Sparse Linear Programming Dynamics of social balance on networks,

Reference 52

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:44:16.498875Z

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Observation 7e66f83a-074c-4fcb-9b32-92ebdec50470 · outbound

This paper cites Bipartite consensus for multi-agent systems on directed signed networks,.

Efficient Learning of Balanced Signed Graphs via Sparse Linear Programming Bipartite consensus for multi-agent systems on directed signed networks,

Reference 53

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:44:16.461695Z

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Observation 357066c2-1e5a-439f-883e-b08b919592ab · outbound

This paper cites The Structural Balance Theory of Sentiment Networks: Elaboration and Test,.

Efficient Learning of Balanced Signed Graphs via Sparse Linear Programming The Structural Balance Theory of Sentiment Networks: Elaboration and Test,

Reference 54

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 679a78fb-1acc-419d-b672-f6f17f5da465 · outbound

This paper cites Testing structural balance theories in heterogeneous signed networks,.

Efficient Learning of Balanced Signed Graphs via Sparse Linear Programming Testing structural balance theories in heterogeneous signed networks,

Reference 55

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:44:16.316171Z

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No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation f67f04d4-7527-402c-b2cf-f5c5d00626e4 · outbound

This paper cites an unresolved cited work.

Efficient Learning of Balanced Signed Graphs via Sparse Linear Programming Unresolved cited work

Reference 56

Resolution: unresolved; raw_fallback, observed 2026-08-07T11:44:15.098439Z

Source-reported events for the cited work

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Observation f335296a-9e78-4e2c-9409-1a04dbd762f3 · outbound

This paper cites Information Theory and an Extension of the Maximum Likelihood Principle,.

Efficient Learning of Balanced Signed Graphs via Sparse Linear Programming Information Theory and an Extension of the Maximum Likelihood Principle,

Reference 57

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:44:15.065131Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 185ede38-e736-4252-9db8-0da7ddf1e775 · outbound

This paper cites Estimating the dimension of a model,.

Efficient Learning of Balanced Signed Graphs via Sparse Linear Programming Estimating the dimension of a model,

Reference 58

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:44:15.012524Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 4c4de849-9f07-4d8f-a1e3-48fee487fe46 · outbound

This paper cites Graph learning information criterion,.

Efficient Learning of Balanced Signed Graphs via Sparse Linear Programming Graph learning information criterion,

Reference 59

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:44:14.969284Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation d95124d2-153d-48b7-bdef-7c0afd1cdfa9 · outbound

This paper cites an unresolved cited work.

Efficient Learning of Balanced Signed Graphs via Sparse Linear Programming Unresolved cited work

Reference 60

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation fc5d0ef1-9534-4468-a5dd-8603f8821156 · outbound

This paper cites An introduction to the conjugate gradient method without the agonizing pain,.

Efficient Learning of Balanced Signed Graphs via Sparse Linear Programming An introduction to the conjugate gradient method without the agonizing pain,

Reference 61

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:44:14.912140Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 4e7c4de0-c1a1-4120-9eff-158a4b407f7d · outbound

This paper cites On random graphs i,.

Efficient Learning of Balanced Signed Graphs via Sparse Linear Programming On random graphs i,

Reference 62

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:44:14.875646Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 4f6aec36-461f-43b7-876f-87d5bed4543e · outbound

This paper cites Untrained Graph Neural Networks for Denoising,.

Efficient Learning of Balanced Signed Graphs via Sparse Linear Programming Untrained Graph Neural Networks for Denoising,

Reference 63

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:44:14.838896Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 80aa9089-746c-4272-99f0-be87c9243dc8 · outbound

This paper cites Biggs, Algebraic graph theory.

Efficient Learning of Balanced Signed Graphs via Sparse Linear Programming Biggs, Algebraic graph theory

Reference 64

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:44:14.801816Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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