Paper Citation Record · LEDGER

A Bundle-based Augmented Lagrangian Framework: Algorithm, Convergence, and Primal-dual Principles

As of 9 August 2026, this Paper Citation Record lists 63 of 63 outbound references and 2 inbound Pith citation observations for arXiv:2502.08835.

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pith.paper-citation-record.v1
2502.08835 v1

Coverage vector

measured 63 of 63 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T23:41:20.458707Z

measured 65 of 65 standing notices

One-hop event checks from named stored sources.

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measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-05T11:32:37.505199Z

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: arxiv_reference, observed 2026-05-22T23:35:13.309563Z

Reference resolution

63 of 63 outbound references displayed

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External citation measurements

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Outbound references

Observation 4971fec3-26a8-4cc0-aadd-fac3ba6ab467 · outbound

This paper cites Convex optimization.

A Bundle-based Augmented Lagrangian Framework: Algorithm, Convergence, and Primal-dual Principles Convex optimization

Reference 1

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Observation b9d9da10-8f4b-42d7-9c4c-fb6f5be2e303 · outbound

This paper cites Handbook of semideﬁnite programming: theory, algorithms, and applications , volume 27.

A Bundle-based Augmented Lagrangian Framework: Algorithm, Convergence, and Primal-dual Principles Handbook of semideﬁnite programming: theory, algorithms, and applications , volume 27

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T23:41:21.340771Z

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Observation 46c3bcbb-ceb8-4847-b04e-cd28f1f05154 · outbound

This paper cites A Primal-Dual Frank-Wolfe Algorithm for Linear Programming.

A Bundle-based Augmented Lagrangian Framework: Algorithm, Convergence, and Primal-dual Principles A Primal-Dual Frank-Wolfe Algorithm for Linear Programming

Reference 3

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Observation ac623cb0-b7af-4c36-9bd7-a1f80616a0e8 · outbound

This paper cites An overview and compa rison of spectral bundle methods for primal and dual semideﬁnite programs.

A Bundle-based Augmented Lagrangian Framework: Algorithm, Convergence, and Primal-dual Principles An overview and compa rison of spectral bundle methods for primal and dual semideﬁnite programs

Reference 4

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Observation 0f446335-ed9b-482a-a8e9-ebfad08200eb · outbound

This paper cites Revisiting spectral bundle metho ds: Primal-dual (sub) linear convergence rates.

A Bundle-based Augmented Lagrangian Framework: Algorithm, Convergence, and Primal-dual Principles Revisiting spectral bundle metho ds: Primal-dual (sub) linear convergence rates

Reference 5

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Observation 949bf6c4-079d-4ba1-963f-768496d8c13b · outbound

This paper cites Scalable semideﬁnite programming.

A Bundle-based Augmented Lagrangian Framework: Algorithm, Convergence, and Primal-dual Principles Scalable semideﬁnite programming

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T23:41:21.317663Z

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Observation e5bcf922-b06c-4e7e-a34a-259747d14d93 · outbound

This paper cites Chordal and factor-width decompo- sitions for scalable semideﬁnite and polynomial optimization.

A Bundle-based Augmented Lagrangian Framework: Algorithm, Convergence, and Primal-dual Principles Chordal and factor-width decompo- sitions for scalable semideﬁnite and polynomial optimization

Reference 7

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Observation 288bd54c-c80c-4d62-915b-58f50d2ced90 · outbound

This paper cites Improved approximation alg orithms for maximum cut and satisﬁability problems using semideﬁnite programming.

A Bundle-based Augmented Lagrangian Framework: Algorithm, Convergence, and Primal-dual Principles Improved approximation alg orithms for maximum cut and satisﬁability problems using semideﬁnite programming

Reference 8

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Observation ed256fc2-94d2-491c-9aee-43532de12d53 · outbound

This paper cites On the constr uction of Lyapunov functions using the sum of squares decomposition.

A Bundle-based Augmented Lagrangian Framework: Algorithm, Convergence, and Primal-dual Principles On the constr uction of Lyapunov functions using the sum of squares decomposition

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T23:41:21.283821Z

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Observation a895ae01-1756-4c8d-9c3e-72147805f29a · outbound

This paper cites Decoding binary node labels from censored edge measurements: Phase transition and eﬃcient recovery.

A Bundle-based Augmented Lagrangian Framework: Algorithm, Convergence, and Primal-dual Principles Decoding binary node labels from censored edge measurements: Phase transition and eﬃcient recovery

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T23:41:21.271854Z

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Observation 483d3191-5dfe-4e10-bc4c-ca88dba00d61 · outbound

This paper cites Phaselift: Exact and stable signal recovery from magnitude measurements via convex programming.

A Bundle-based Augmented Lagrangian Framework: Algorithm, Convergence, and Primal-dual Principles Phaselift: Exact and stable signal recovery from magnitude measurements via convex programming

Reference 11

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Observation c7b23fb8-c776-45ae-8856-5fd4c16bf2c0 · outbound

This paper cites Low-rank matrix recovery from errors and erasures.

A Bundle-based Augmented Lagrangian Framework: Algorithm, Convergence, and Primal-dual Principles Low-rank matrix recovery from errors and erasures

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T23:41:21.248103Z

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Observation 0ca04601-96bb-4dc5-a83e-35c1ab535dae · outbound

This paper cites PEPit: computer-assisted worst-case analyses of ﬁr st-order optimization methods in Python.

A Bundle-based Augmented Lagrangian Framework: Algorithm, Convergence, and Primal-dual Principles PEPit: computer-assisted worst-case analyses of ﬁr st-order optimization methods in Python

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T23:41:21.236289Z

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Observation 40006afa-5fce-442c-a4e3-ae959dbf8ae6 · outbound

This paper cites On the scalability and memory eﬃciency of semideﬁnite programs for L ipschitz constant estimation of neural networks.

A Bundle-based Augmented Lagrangian Framework: Algorithm, Convergence, and Primal-dual Principles On the scalability and memory eﬃciency of semideﬁnite programs for L ipschitz constant estimation of neural networks

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T23:41:21.223872Z

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Observation 21e92e8d-4659-4ffb-bcd3-56bc67b60860 · outbound

This paper cites Augmented Lagrangians and applications of the proximal point algorithm in convex programming.

A Bundle-based Augmented Lagrangian Framework: Algorithm, Convergence, and Primal-dual Principles Augmented Lagrangians and applications of the proximal point algorithm in convex programming

Reference 15

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Observation 5d6b91e2-1484-44a6-9353-194e43a6fe23 · outbound

This paper cites Multiplier and gradient methods.

A Bundle-based Augmented Lagrangian Framework: Algorithm, Convergence, and Primal-dual Principles Multiplier and gradient methods

Reference 16

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Observation 7213ef7e-425f-4adb-89a8-50403e919580 · outbound

This paper cites A method for nonlinear constraints in minimizatio n problems.

A Bundle-based Augmented Lagrangian Framework: Algorithm, Convergence, and Primal-dual Principles A method for nonlinear constraints in minimizatio n problems

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T23:41:21.182938Z

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Observation 18b8ba85-0ef5-4a19-a468-6ffbb68c0949 · outbound

This paper cites Monotone operators and the proximal p oint algorithm.

A Bundle-based Augmented Lagrangian Framework: Algorithm, Convergence, and Primal-dual Principles Monotone operators and the proximal p oint algorithm

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T23:41:21.169558Z

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Observation 9c15e9e0-f2da-48a6-8c42-6dbe33818e1e · outbound

This paper cites Asymptotic convergence analysis of t he proximal point algorithm.

A Bundle-based Augmented Lagrangian Framework: Algorithm, Convergence, and Primal-dual Principles Asymptotic convergence analysis of t he proximal point algorithm

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T23:41:21.155937Z

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Observation 95869dfc-188b-4b47-b830-0db3817e75ec · outbound

This paper cites On the R-superlinear c onvergence of the KKT residuals generated by the augmented Lagrangian method for convex comp osite conic programming.

A Bundle-based Augmented Lagrangian Framework: Algorithm, Convergence, and Primal-dual Principles On the R-superlinear c onvergence of the KKT residuals generated by the augmented Lagrangian method for convex comp osite conic programming

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T23:41:21.139665Z

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Observation 51ec75e0-6d2c-4928-9842-e09ba144fb8d · outbound

This paper cites Iteration complexity of inexact augmented Lagr angian methods for constrained convex programming.

A Bundle-based Augmented Lagrangian Framework: Algorithm, Convergence, and Primal-dual Principles Iteration complexity of inexact augmented Lagr angian methods for constrained convex programming

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T23:41:21.125894Z

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Observation e3df9c21-3f92-45a1-a3ad-50566cbf3cef · outbound

This paper cites Inexact augmented Lagrangian methods for conic opti- mization: Quadratic growth and linear convergence.

A Bundle-based Augmented Lagrangian Framework: Algorithm, Convergence, and Primal-dual Principles Inexact augmented Lagrangian methods for conic opti- mization: Quadratic growth and linear convergence

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T23:41:21.109264Z

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Observation c5864a9b-21b6-474c-a326-e26c16e6705b · outbound

This paper cites A se mismooth Newton-CG based dual PPA for matrix spectral norm approximation problems.

A Bundle-based Augmented Lagrangian Framework: Algorithm, Convergence, and Primal-dual Principles A se mismooth Newton-CG based dual PPA for matrix spectral norm approximation problems

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T23:41:21.096650Z

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Observation 756df456-e2ef-4e70-9e18-6413b48ad9bb · outbound

This paper cites Sdpnal+: A matlab software for semideﬁnite programming with bound constraints (version 1.0).

A Bundle-based Augmented Lagrangian Framework: Algorithm, Convergence, and Primal-dual Principles Sdpnal+: A matlab software for semideﬁnite programming with bound constraints (version 1.0)

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T23:41:21.084775Z

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Observation 78beae6e-abf7-4d37-bdc9-92ed8c6c7c84 · outbound

This paper cites A conditional- gradient-based augmented Lagrangian framework.

A Bundle-based Augmented Lagrangian Framework: Algorithm, Convergence, and Primal-dual Principles A conditional- gradient-based augmented Lagrangian framework

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T23:41:21.073539Z

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Observation 52fcd9b6-b389-43aa-b24f-1d4640ef6e56 · outbound

This paper cites A fast iterative shrinkage-thresh olding algorithm for linear inverse problems.

A Bundle-based Augmented Lagrangian Framework: Algorithm, Convergence, and Primal-dual Principles A fast iterative shrinkage-thresh olding algorithm for linear inverse problems

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T23:41:21.061682Z

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Observation 8e497f93-c3f2-407c-999e-d6b0c1448515 · outbound

This paper cites An algorithm for quadratic p rogramming.

A Bundle-based Augmented Lagrangian Framework: Algorithm, Convergence, and Primal-dual Principles An algorithm for quadratic p rogramming

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T23:41:21.049250Z

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Observation 145ed672-73e2-41d9-aebd-a4aabc1f73ef · outbound

This paper cites Sdpnal+: a majoriz ed semismooth Newton-CG aug- mented Lagrangian method for semideﬁnite programming with nonne gative constraints.

A Bundle-based Augmented Lagrangian Framework: Algorithm, Convergence, and Primal-dual Principles Sdpnal+: a majoriz ed semismooth Newton-CG aug- mented Lagrangian method for semideﬁnite programming with nonne gative constraints

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T23:41:21.037457Z

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Observation a14c9551-b447-48ed-b146-a60d54b97f78 · outbound

This paper cites A Newton-CG a ugmented Lagrangian method for semideﬁnite programming.

A Bundle-based Augmented Lagrangian Framework: Algorithm, Convergence, and Primal-dual Principles A Newton-CG a ugmented Lagrangian method for semideﬁnite programming

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T23:41:21.024274Z

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Observation 74db9424-15c1-4672-a36e-1a0001f0ba55 · outbound

This paper cites Iteration-complexity o f ﬁrst-order augmented Lagrangian methods for convex programming.

A Bundle-based Augmented Lagrangian Framework: Algorithm, Convergence, and Primal-dual Principles Iteration-complexity o f ﬁrst-order augmented Lagrangian methods for convex programming

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T23:41:21.010475Z

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Observation a743ff49-ab99-41e2-98c7-7a0a843a1cb0 · outbound

This paper cites Sum of squares basis pursuit wit h linear and second order cone programming.

A Bundle-based Augmented Lagrangian Framework: Algorithm, Convergence, and Primal-dual Principles Sum of squares basis pursuit wit h linear and second order cone programming

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T23:41:20.997188Z

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Observation 5fee61b0-e6b3-4e66-bcd7-02714d50ad25 · outbound

This paper cites Bloc k factor-width-two matrices and their applications to semideﬁnite and sum-of-squares optimization.

A Bundle-based Augmented Lagrangian Framework: Algorithm, Convergence, and Primal-dual Principles Bloc k factor-width-two matrices and their applications to semideﬁnite and sum-of-squares optimization

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T23:41:20.983947Z

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Observation 1fed23b3-be16-47ab-8225-7ac2cbe7b018 · outbound

This paper cites Iterative inner/outer approxim ations for scalable semideﬁnite programs using block factor-width-two matrices.

A Bundle-based Augmented Lagrangian Framework: Algorithm, Convergence, and Primal-dual Principles Iterative inner/outer approxim ations for scalable semideﬁnite programs using block factor-width-two matrices

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T23:41:20.970702Z

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Observation 15a34116-d86b-40bf-9dec-72b1f9befc76 · outbound

This paper cites A nonlinear programming algorithm for solving semideﬁnite programs via low-rank factorization.

A Bundle-based Augmented Lagrangian Framework: Algorithm, Convergence, and Primal-dual Principles A nonlinear programming algorithm for solving semideﬁnite programs via low-rank factorization

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T23:41:20.955612Z

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No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation cdd35851-5265-43ca-994e-c9ba9719d452 · outbound

This paper cites A low-rank augmented Lagrangian method for large-scale semidefinite programming based on a hybrid convex-nonconvex approach.

A Bundle-based Augmented Lagrangian Framework: Algorithm, Convergence, and Primal-dual Principles A low-rank augmented Lagrangian method for large-scale semidefinite programming based on a hybrid convex-nonconvex approach

Reference 35

Resolution: unresolved; no resolver link, observed 2026-08-07T23:41:20.345193Z

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Observation b1ddc781-f46c-488f-bcc8-c8c4a714793f · outbound

This paper cites A feasible method for general convex low-rank SDP problems.

A Bundle-based Augmented Lagrangian Framework: Algorithm, Convergence, and Primal-dual Principles A feasible method for general convex low-rank SDP problems

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T23:41:20.939921Z

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Observation de5bfb03-2397-4b67-a199-117e69d70921 · outbound

This paper cites A dec omposition augmented lagrangian method for low-rank semideﬁnite programming.

A Bundle-based Augmented Lagrangian Framework: Algorithm, Convergence, and Primal-dual Principles A dec omposition augmented lagrangian method for low-rank semideﬁnite programming

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T23:41:20.925648Z

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Observation 8731ea68-d284-4d82-89e9-0c9d88160c1f · outbound

This paper cites Optimal convergence ratesfor the proximal bundle method.

A Bundle-based Augmented Lagrangian Framework: Algorithm, Convergence, and Primal-dual Principles Optimal convergence ratesfor the proximal bundle method

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T23:41:20.911675Z

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Observation 89e82393-0480-47e1-bd23-820fd8a37e4c · outbound

This paper cites Faster projec tion-free augmented Lagrangian methods via weak proximal oracle.

A Bundle-based Augmented Lagrangian Framework: Algorithm, Convergence, and Primal-dual Principles Faster projec tion-free augmented Lagrangian methods via weak proximal oracle

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T23:41:20.898626Z

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Observation 08d85cee-e0ea-4c4a-b0c5-081be52cdfda · outbound

This paper cites On the nonergodic converge nce rate of an inexact aug- mented Lagrangian framework for composite convex programming.

A Bundle-based Augmented Lagrangian Framework: Algorithm, Convergence, and Primal-dual Principles On the nonergodic converge nce rate of an inexact aug- mented Lagrangian framework for composite convex programming

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T23:41:20.885333Z

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Observation 565db868-80fc-4d0b-8d97-6e2e2d2908c8 · outbound

This paper cites Practical augmented Lagrangian methods for constrained optimization.

A Bundle-based Augmented Lagrangian Framework: Algorithm, Convergence, and Primal-dual Principles Practical augmented Lagrangian methods for constrained optimization

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T23:41:20.871979Z

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Observation 77bfefb8-2abb-4f57-b78d-2c186380f264 · outbound

This paper cites Metric subregularity and the proximal point metho d.

A Bundle-based Augmented Lagrangian Framework: Algorithm, Convergence, and Primal-dual Principles Metric subregularity and the proximal point metho d

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T23:41:20.858383Z

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Observation 6d23ebdd-776d-4edf-aa38-21a9d00f3422 · outbound

This paper cites First-order methods in optimization.

A Bundle-based Augmented Lagrangian Framework: Algorithm, Convergence, and Primal-dual Principles First-order methods in optimization

Reference 43

Resolution: unresolved; no resolver link, observed 2026-08-07T23:41:20.377365Z

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Observation 167216fa-08b3-4772-b925-4436bdeeeca6 · outbound

This paper cites A condensed introductio n to bundle methods in nonsmooth optimization.

A Bundle-based Augmented Lagrangian Framework: Algorithm, Convergence, and Primal-dual Principles A condensed introductio n to bundle methods in nonsmooth optimization

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T23:41:20.837563Z

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Observation 221ce05f-ed4d-4aab-86c3-2b851f2c6854 · outbound

This paper cites Learning the kernel matrix with semideﬁnite programming.

A Bundle-based Augmented Lagrangian Framework: Algorithm, Convergence, and Primal-dual Principles Learning the kernel matrix with semideﬁnite programming

Reference 45

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T23:41:20.824985Z

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Observation 4d287192-9682-4f60-8c89-388bd0749ccb · outbound

This paper cites On approximations of the psd c one by a polynomial number of smaller-sized psd cones.

A Bundle-based Augmented Lagrangian Framework: Algorithm, Convergence, and Primal-dual Principles On approximations of the psd c one by a polynomial number of smaller-sized psd cones

Reference 46

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T23:41:20.812463Z

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Observation 507ca458-091e-466b-9f0e-37a5c7efc58a · outbound

This paper cites Nonlinear optimization.

A Bundle-based Augmented Lagrangian Framework: Algorithm, Convergence, and Primal-dual Principles Nonlinear optimization

Reference 47

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This paper cites Error bounds, pl co ndition, and quadratic growth for weakly convex functions, and linear convergences of proximal poin t methods.

A Bundle-based Augmented Lagrangian Framework: Algorithm, Convergence, and Primal-dual Principles Error bounds, pl co ndition, and quadratic growth for weakly convex functions, and linear convergences of proximal poin t methods

Reference 48

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This paper cites A spectral bundle method for semideﬁnite programming.

A Bundle-based Augmented Lagrangian Framework: Algorithm, Convergence, and Primal-dual Principles A spectral bundle method for semideﬁnite programming

Reference 49

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This paper cites Quadratic growth conditio ns for convex matrix optimization problems associated with spectral functions.

A Bundle-based Augmented Lagrangian Framework: Algorithm, Convergence, and Primal-dual Principles Quadratic growth conditio ns for convex matrix optimization problems associated with spectral functions

Reference 50

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This paper cites Exact matrix completion via convex optimization.

A Bundle-based Augmented Lagrangian Framework: Algorithm, Convergence, and Primal-dual Principles Exact matrix completion via convex optimization

Reference 51

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This paper cites Second-order cone progra mming.

A Bundle-based Augmented Lagrangian Framework: Algorithm, Convergence, and Primal-dual Principles Second-order cone progra mming

Reference 52

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This paper cites Convex analysis , volume 11.

A Bundle-based Augmented Lagrangian Framework: Algorithm, Convergence, and Primal-dual Principles Convex analysis , volume 11

Reference 53

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This paper cites Gradient methods for minimizing composite functio ns.

A Bundle-based Augmented Lagrangian Framework: Algorithm, Convergence, and Primal-dual Principles Gradient methods for minimizing composite functio ns

Reference 54

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This paper cites Revisiting frank-wolfe: Projection-free sparse convex optimization.

A Bundle-based Augmented Lagrangian Framework: Algorithm, Convergence, and Primal-dual Principles Revisiting frank-wolfe: Projection-free sparse convex optimization

Reference 55

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This paper cites Spectr al frank-wolfe algorithm: Strict complementarity and linear convergence.

A Bundle-based Augmented Lagrangian Framework: Algorithm, Convergence, and Primal-dual Principles Spectr al frank-wolfe algorithm: Strict complementarity and linear convergence

Reference 56

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This paper cites On the Asymptotic Superlinear Convergence of the Augmented Lagrangian Method for Semidefinite Programming with Multiple Solutions.

A Bundle-based Augmented Lagrangian Framework: Algorithm, Convergence, and Primal-dual Principles On the Asymptotic Superlinear Convergence of the Augmented Lagrangian Method for Semidefinite Programming with Multiple Solutions

Reference 57

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A Bundle-based Augmented Lagrangian Framework: Algorithm, Convergence, and Primal-dual Principles The MOSEK optimization toolbox for MATLAB manual

Reference 58

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This paper cites On the simplicity and conditioning of low rank semideﬁnite programs.

A Bundle-based Augmented Lagrangian Framework: Algorithm, Convergence, and Primal-dual Principles On the simplicity and conditioning of low rank semideﬁnite programs

Reference 59

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This paper cites Global optimization with polynomials and the pro blem of moments.

A Bundle-based Augmented Lagrangian Framework: Algorithm, Convergence, and Primal-dual Principles Global optimization with polynomials and the pro blem of moments

Reference 60

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This paper cites In particular, as we will see in ( B.1), it holds that − min x∈ Ω k Lρ(x, yk) = min y∈ Rm gk(y) + 1 2ρ ‖y − yk‖2.

A Bundle-based Augmented Lagrangian Framework: Algorithm, Convergence, and Primal-dual Principles In particular, as we will see in ( B.1), it holds that − min x∈ Ω k Lρ(x, yk) = min y∈ Rm gk(y) + 1 2ρ ‖y − yk‖2

Reference 61

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This paper cites Finally, our bundle -based Augmented Lagrangian framework also complements the viewpoints of interior-point and penalty m ethods [1, Chapter 11] in addressing Ω.

A Bundle-based Augmented Lagrangian Framework: Algorithm, Convergence, and Primal-dual Principles Finally, our bundle -based Augmented Lagrangian framework also complements the viewpoints of interior-point and penalty m ethods [1, Chapter 11] in addressing Ω

Reference 62

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This paper cites The convex hull app roximation with three points always contains the line approximation.

A Bundle-based Augmented Lagrangian Framework: Algorithm, Convergence, and Primal-dual Principles The convex hull app roximation with three points always contains the line approximation

Reference 63

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Local Linear Convergence of the Alternating Direction Method of Multipliers for Semidefinite Programming under Strict Complementarity cites this paper.

Local Linear Convergence of the Alternating Direction Method of Multipliers for Semidefinite Programming under Strict Complementarity A Bundle-based Augmented Lagrangian Framework: Algorithm, Convergence, and Primal-dual Principles

Reference 38

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A Proximal Descent Method for Minimizing Weakly Convex Optimization cites this paper.

A Proximal Descent Method for Minimizing Weakly Convex Optimization A Bundle-based Augmented Lagrangian Framework: Algorithm, Convergence, and Primal-dual Principles

Reference 17

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