Paper Citation Record · LEDGER

Establishing Boundary KKT Convergence of Mirror Descent through Reparameterization

As of 10 August 2026, this Paper Citation Record lists 35 of 35 outbound references and 0 inbound Pith citation observations for arXiv:2608.07248.

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

pith.paper-citation-record.v1
2608.07248 v1

Coverage vector

measured 35 of 35 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-10T12:00:38.314620Z

measured 35 of 35 standing notices

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Source: scholarly_work_events, retraction_status_cache, observed 2026-08-10T06:31:04.303077+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

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measured 0 of 1 external citation measurements

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Source: cited_works

Reference resolution

35 of 35 outbound references displayed

verified exact1
verified fuzzy24
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External citation measurements

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Outbound references

Observation 2395d21b-b057-4718-9a3e-f4c89487c3c1 · outbound

This paper cites Hessian Riemannian gradient flows in convex programming.

Establishing Boundary KKT Convergence of Mirror Descent through Reparameterization Hessian Riemannian gradient flows in convex programming

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T12:00:49.100717Z

Source-reported events for the cited work

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

Observation fc605745-f60d-474f-a1fa-9778fe004b99 · outbound

This paper cites Singular Riemannian barrier methods and gradient-projection dynamical systems for constrained optimization.Optimization, 53(5–6):435–454, 2004.

Establishing Boundary KKT Convergence of Mirror Descent through Reparameterization Singular Riemannian barrier methods and gradient-projection dynamical systems for constrained optimization.Optimization, 53(5–6):435–454, 2004

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T12:00:49.076375Z

Source-reported events for the cited work

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

Observation 5ec4009b-b824-4855-933a-cc31e520f065 · outbound

This paper cites an unresolved cited work.

Establishing Boundary KKT Convergence of Mirror Descent through Reparameterization Unresolved cited work

Reference 3

Resolution: unresolved; raw_fallback, observed 2026-08-10T12:00:49.052031Z

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

Observation fc19c3ed-575f-4a8a-8760-be0e9dfdc816 · outbound

This paper cites Bauschke, J´ erˆ ome Bolte, and Marc Teboulle.

Establishing Boundary KKT Convergence of Mirror Descent through Reparameterization Bauschke, J´ erˆ ome Bolte, and Marc Teboulle

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T12:00:49.028854Z

Source-reported events for the cited work

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

Observation 1340cf75-28b7-435a-b904-1c1a8ab7b4a3 · outbound

This paper cites an unresolved cited work.

Establishing Boundary KKT Convergence of Mirror Descent through Reparameterization Unresolved cited work

Reference 5

Resolution: unresolved; raw_fallback, observed 2026-08-10T12:00:49.009436Z

Source-reported events for the cited work

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

Observation b9e54e9c-c870-43fe-9685-f5602855f4d2 · outbound

This paper cites Lewis, and Masahiro Shiota.

Establishing Boundary KKT Convergence of Mirror Descent through Reparameterization Lewis, and Masahiro Shiota

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T12:00:48.991747Z

Source-reported events for the cited work

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

Observation caed55d7-cc94-4193-8ffd-9bf3a9f2c79c · outbound

This paper cites Curiosities and counterexamples in smooth convex optimization.Mathematical Programming, 195(1–2):553–603, 2022.

Establishing Boundary KKT Convergence of Mirror Descent through Reparameterization Curiosities and counterexamples in smooth convex optimization.Mathematical Programming, 195(1–2):553–603, 2022

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T12:00:48.974172Z

Source-reported events for the cited work

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

Observation 8380ba9e-b238-4211-996d-de70a9279bae · outbound

This paper cites First order methods beyond convexity and Lipschitz gradient continuity with applications to quadratic inverse problems.SIAM Journal on Optimization, 28(3):2131–2151, 2018.

Establishing Boundary KKT Convergence of Mirror Descent through Reparameterization First order methods beyond convexity and Lipschitz gradient continuity with applications to quadratic inverse problems.SIAM Journal on Optimization, 28(3):2131–2151, 2018

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-10T12:00:38.143148Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9be3e07c-4fbc-47b9-8d2a-4a187d8a07c0 · outbound

This paper cites Bomze, Panayotis Mertikopoulos, Werner Schachinger, and Mathias Staudigl.

Establishing Boundary KKT Convergence of Mirror Descent through Reparameterization Bomze, Panayotis Mertikopoulos, Werner Schachinger, and Mathias Staudigl

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T12:00:48.939233Z

Source-reported events for the cited work

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

Observation 6e28424d-f28a-4d9d-a5ee-3af5a621518f · outbound

This paper cites Spurious Stationarity and Hardness Results for Bregman Proximal-Type Algorithms.

Establishing Boundary KKT Convergence of Mirror Descent through Reparameterization Spurious Stationarity and Hardness Results for Bregman Proximal-Type Algorithms

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-10T12:00:38.154467Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e231797e-e820-4884-91fc-9a36679ca328 · outbound

This paper cites On the Iterate Convergence of Bregman Projected Gradient Method.

Establishing Boundary KKT Convergence of Mirror Descent through Reparameterization On the Iterate Convergence of Bregman Projected Gradient Method

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-10T12:00:38.160589Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 86845fd0-677b-439b-bf46-f5b9f73d66ee · outbound

This paper cites Sinkhorn distances: Lightspeed computation of optimal transport.

Establishing Boundary KKT Convergence of Mirror Descent through Reparameterization Sinkhorn distances: Lightspeed computation of optimal transport

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T12:00:48.917692Z

Source-reported events for the cited work

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

Observation 00a7e46a-c67a-4f50-aca0-5922e2f95960 · outbound

This paper cites Dang and Guanghui Lan.

Establishing Boundary KKT Convergence of Mirror Descent through Reparameterization Dang and Guanghui Lan

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T12:00:48.898550Z

Source-reported events for the cited work

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

Observation 55f8c75b-f11d-4d06-8cee-f9268a6f3f7b · outbound

This paper cites Nonconvex stochastic Bregman proximal gradient method with application to deep learning.Journal of Machine Learning Research, 26(39):1–44, 2025.

Establishing Boundary KKT Convergence of Mirror Descent through Reparameterization Nonconvex stochastic Bregman proximal gradient method with application to deep learning.Journal of Machine Learning Research, 26(39):1–44, 2025

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T12:00:48.878460Z

Source-reported events for the cited work

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

Observation 2f460f4b-7463-4563-800e-aa4fb773ddf0 · outbound

This paper cites On exploration of an interior mirror descent flow for stochastic nonconvex constrained problem.

Establishing Boundary KKT Convergence of Mirror Descent through Reparameterization On exploration of an interior mirror descent flow for stochastic nonconvex constrained problem

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-10T12:00:38.185645Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 952e0195-e9d1-49be-b42e-6fdb15f4b32c · outbound

This paper cites Non-KKT Accumulation in Entropic Mirror Descent.

Establishing Boundary KKT Convergence of Mirror Descent through Reparameterization Non-KKT Accumulation in Entropic Mirror Descent

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-10T12:00:38.191837Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5e8a6288-8be7-4a1c-9b4f-e55b1852209e · outbound

This paper cites Doan, Subhonmesh Bose, D.

Establishing Boundary KKT Convergence of Mirror Descent through Reparameterization Doan, Subhonmesh Bose, D

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T12:00:48.858451Z

Source-reported events for the cited work

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

Observation 0eda8218-ef94-4ede-8339-456737b8dce3 · outbound

This paper cites A bregman ADMM for Bethe variational problem.arXiv preprint arXiv:2502.04613, 2025.

Establishing Boundary KKT Convergence of Mirror Descent through Reparameterization A bregman ADMM for Bethe variational problem.arXiv preprint arXiv:2502.04613, 2025

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-10T12:00:38.204852Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 99e70ec5-11de-447f-9360-4674b09f0d22 · outbound

This paper cites On gradients of functions definable in O-minimal structures.Annales de l’Institut Fourier, 48(3):769–783, 1998.

Establishing Boundary KKT Convergence of Mirror Descent through Reparameterization On gradients of functions definable in O-minimal structures.Annales de l’Institut Fourier, 48(3):769–783, 1998

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T12:00:48.836113Z

Source-reported events for the cited work

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

Observation b27ca811-c157-4165-b77f-c98dd98db449 · outbound

This paper cites A convergent single-loop algorithm for relaxation of Gromov–Wasserstein in graph data.

Establishing Boundary KKT Convergence of Mirror Descent through Reparameterization A convergent single-loop algorithm for relaxation of Gromov–Wasserstein in graph data

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T12:00:48.815786Z

Source-reported events for the cited work

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

Observation 97a3806d-1bba-40b0-b9a1-20919fc8da89 · outbound

This paper cites Convergence of the exponentiated gradient method with Armijo line search.

Establishing Boundary KKT Convergence of Mirror Descent through Reparameterization Convergence of the exponentiated gradient method with Armijo line search

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T12:00:48.795434Z

Source-reported events for the cited work

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

Observation 8d679168-af54-4cd9-bdfb-43c4333cd8e9 · outbound

This paper cites Lee, and Sanjeev Arora.

Establishing Boundary KKT Convergence of Mirror Descent through Reparameterization Lee, and Sanjeev Arora

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T12:00:48.777457Z

Source-reported events for the cited work

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

Observation 6adfe90f-57f3-4c68-95f2-f2c2b7981967 · outbound

This paper cites Gromov–Wasserstein distances and the metric approach to object matching.Foundations of Computational Mathematics, 11(4):417–487, 2011.

Establishing Boundary KKT Convergence of Mirror Descent through Reparameterization Gromov–Wasserstein distances and the metric approach to object matching.Foundations of Computational Mathematics, 11(4):417–487, 2011

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T12:00:48.759812Z

Source-reported events for the cited work

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

Observation 0d9cfe2b-b959-4421-b4e7-598d14293201 · outbound

This paper cites Global convergence of model function based Bregman proximal minimization algorithms.Journal of Global Optimization, 83(4):753–781, 2022.

Establishing Boundary KKT Convergence of Mirror Descent through Reparameterization Global convergence of model function based Bregman proximal minimization algorithms.Journal of Global Optimization, 83(4):753–781, 2022

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T12:00:48.739864Z

Source-reported events for the cited work

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

Observation 5d0aa69d-d2e0-4c12-b3f8-42bdcf18f7fa · outbound

This paper cites Elementary vectors and conformal sums in polyhedral geometry and their relevance for metabolic pathway analysis.Frontiers in Genetics, 7:90, 2016.

Establishing Boundary KKT Convergence of Mirror Descent through Reparameterization Elementary vectors and conformal sums in polyhedral geometry and their relevance for metabolic pathway analysis.Frontiers in Genetics, 7:90, 2016

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T12:00:48.716950Z

Source-reported events for the cited work

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

Observation 50ec6348-8016-4844-942a-56b9cd503a05 · outbound

This paper cites Computational optimal transport.Foundations and Trends in Machine Learning, 11(5–6):355–607, 2019.

Establishing Boundary KKT Convergence of Mirror Descent through Reparameterization Computational optimal transport.Foundations and Trends in Machine Learning, 11(5–6):355–607, 2019

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T12:00:48.699063Z

Source-reported events for the cited work

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

Observation a49db340-8942-45fe-bd18-62ee9ba414f6 · outbound

This paper cites Gromov–Wasserstein averaging of kernel and distance matrices.

Establishing Boundary KKT Convergence of Mirror Descent through Reparameterization Gromov–Wasserstein averaging of kernel and distance matrices

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T12:00:48.681098Z

Source-reported events for the cited work

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

Observation 25192ee9-5391-4892-8684-8a66ac4ca225 · outbound

This paper cites Shuffling the stochastic mirror descent via dual lipschitz continuity and kernel conditioning.arXiv preprint arXiv:2603.16042, 2026.

Establishing Boundary KKT Convergence of Mirror Descent through Reparameterization Shuffling the stochastic mirror descent via dual lipschitz continuity and kernel conditioning.arXiv preprint arXiv:2603.16042, 2026

Reference 28

Resolution: verified exact; arxiv_id, observed 2026-08-10T12:00:42.957242Z

Source-reported events for the cited work

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

Observation 515849f7-4eb6-476e-8480-c3e7309a2ca2 · outbound

This paper cites Entropic Gromov–Wasserstein distances: Stability and algorithms.

Establishing Boundary KKT Convergence of Mirror Descent through Reparameterization Entropic Gromov–Wasserstein distances: Stability and algorithms

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T12:00:48.664178Z

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

Observation 56f0a5fb-a9f9-49c0-9c61-b104f2f7a599 · outbound

This paper cites Tyrrell Rockafellar.

Establishing Boundary KKT Convergence of Mirror Descent through Reparameterization Tyrrell Rockafellar

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T12:00:48.647170Z

Source-reported events for the cited work

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

Observation 291f4f49-baf5-496a-adfc-5928ed655869 · outbound

This paper cites Tyrrell Rockafellar.Convex Analysis, volume 28 ofPrinceton Mathematical Series.

Establishing Boundary KKT Convergence of Mirror Descent through Reparameterization Tyrrell Rockafellar.Convex Analysis, volume 28 ofPrinceton Mathematical Series

Reference 31

Resolution: unresolved; no resolver link, observed 2026-08-10T12:00:38.287702Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 294ab114-23fb-4dfa-9723-e060f427f54e · outbound

This paper cites Tyrrell Rockafellar and Roger J.-B.

Establishing Boundary KKT Convergence of Mirror Descent through Reparameterization Tyrrell Rockafellar and Roger J.-B

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T12:00:48.617651Z

Source-reported events for the cited work

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

Observation 52e41fa3-6bac-42c1-bcef-e17b74030c79 · outbound

This paper cites Linear-time Gromov–Wasserstein distances using low-rank couplings and costs.

Establishing Boundary KKT Convergence of Mirror Descent through Reparameterization Linear-time Gromov–Wasserstein distances using low-rank couplings and costs

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T12:00:48.600574Z

Source-reported events for the cited work

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

Observation 98c4e22b-6c1f-4103-9073-981cfa5d0f6c · outbound

This paper cites On the Convergence Rate of Stochastic Mirror Descent for Nonsmooth Nonconvex Optimization.

Establishing Boundary KKT Convergence of Mirror Descent through Reparameterization On the Convergence Rate of Stochastic Mirror Descent for Nonsmooth Nonconvex Optimization

Reference 34

Resolution: unresolved; no resolver link, observed 2026-08-10T12:00:38.308592Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4e443594-e486-40ce-8b21-b4e8bae3433a · outbound

This paper cites Boyd, and Peter W.

Establishing Boundary KKT Convergence of Mirror Descent through Reparameterization Boyd, and Peter W

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T12:00:48.582337Z

Source-reported events for the cited work

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

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