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Paper Citation Record · LEDGER

Mirror Descent Methods for Quasar Convex Optimization Problems With Non-Smooth Inequality Constraints

As of 9 August 2026, this Paper Citation Record lists 39 of 39 outbound references and 0 inbound Pith citation observations for arXiv:2607.22551.

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

pith.paper-citation-record.v1
2607.22551 v1

Coverage vector

measured 39 of 39 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-02T14:05:55.721700Z

measured 39 of 39 standing notices

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Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+00:00

measured 0 of 0 inbound itemization

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measured 0 of 1 external citation measurements

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Reference resolution

39 of 39 outbound references displayed

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  • verified fuzzy0
  • unresolved35
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External citation measurements

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Outbound references

Observation fe2baea6-aea3-4881-87d1-414f876d3580 · outbound

This paper cites an unresolved cited work.

Mirror Descent Methods for Quasar Convex Optimization Problems With Non-Smooth Inequality Constraints Unresolved cited work

Reference 1

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Observation 25a3c344-cd72-4d03-b1fb-21c2697256e0 · outbound

This paper cites On some stochastic mirror descent methods for constrained online op- timization problems.

Mirror Descent Methods for Quasar Convex Optimization Problems With Non-Smooth Inequality Constraints On some stochastic mirror descent methods for constrained online op- timization problems

Reference 2

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Observation 8d530593-9270-4b76-8bd4-a81c80183f8b · outbound

This paper cites Quasar-Convex Optimization: Fundamental Properties and High-Order Proximal-Point Methods.

Mirror Descent Methods for Quasar Convex Optimization Problems With Non-Smooth Inequality Constraints Quasar-Convex Optimization: Fundamental Properties and High-Order Proximal-Point Methods

Reference 3

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Observation 22fe223b-f56e-4f58-b90b-33a1ce8dfc85 · outbound

This paper cites Bayandina, P.

Mirror Descent Methods for Quasar Convex Optimization Problems With Non-Smooth Inequality Constraints Bayandina, P

Reference 4

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Observation f9340f49-3f1b-45a7-b81d-844640c95d21 · outbound

This paper cites Bayandina: Adaptive Stochastic Mirror Descent for Constrained Optimization.

Mirror Descent Methods for Quasar Convex Optimization Problems With Non-Smooth Inequality Constraints Bayandina: Adaptive Stochastic Mirror Descent for Constrained Optimization

Reference 5

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Observation 9cde009c-e9ab-4fb1-abf5-952e2a06b29e · outbound

This paper cites Ben-Tal, A.

Mirror Descent Methods for Quasar Convex Optimization Problems With Non-Smooth Inequality Constraints Ben-Tal, A

Reference 6

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Observation e64a306a-bfc4-4642-9b82-4be379c87f19 · outbound

This paper cites an unresolved cited work.

Mirror Descent Methods for Quasar Convex Optimization Problems With Non-Smooth Inequality Constraints Unresolved cited work

Reference 7

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Observation afb2a55e-55be-4ac3-a435-c1e1ab61f7a4 · outbound

This paper cites Extending Linear Convergence of the Proximal Point Algorithm: The Quasar-Convex Case.

Mirror Descent Methods for Quasar Convex Optimization Problems With Non-Smooth Inequality Constraints Extending Linear Convergence of the Proximal Point Algorithm: The Quasar-Convex Case

Reference 8

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Observation c02766d4-122f-422e-9ffb-86f80371b726 · outbound

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Mirror Descent Methods for Quasar Convex Optimization Problems With Non-Smooth Inequality Constraints Unresolved cited work

Reference 9

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Observation 978b7a9f-3754-4e53-9727-a3723a98bc31 · outbound

This paper cites A Continuized View on Nesterov Acceleration for Stochastic Gradient Descent and Randomized Gossip.

Mirror Descent Methods for Quasar Convex Optimization Problems With Non-Smooth Inequality Constraints A Continuized View on Nesterov Acceleration for Stochastic Gradient Descent and Randomized Gossip

Reference 10

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Observation a0c4c4b3-14d5-4022-98c4-e1d3fb81efe5 · outbound

This paper cites Minimisation of Quasar-Convex Functions Using Random Zeroth-Order Oracles.

Mirror Descent Methods for Quasar Convex Optimization Problems With Non-Smooth Inequality Constraints Minimisation of Quasar-Convex Functions Using Random Zeroth-Order Oracles

Reference 11

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Observation 17a9ceaf-05f1-4330-ba1d-67c0c9fab569 · outbound

This paper cites Fercoq, A.

Mirror Descent Methods for Quasar Convex Optimization Problems With Non-Smooth Inequality Constraints Fercoq, A

Reference 12

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Observation 11ad4b42-7313-4fbc-a0f5-7983e8886c90 · outbound

This paper cites Uniform Convergence of Gradients for Non-Convex Learning and Optimization.

Mirror Descent Methods for Quasar Convex Optimization Problems With Non-Smooth Inequality Constraints Uniform Convergence of Gradients for Non-Convex Learning and Optimization

Reference 13

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Observation 9be2c452-e1b6-4b9c-8f7b-4c47997fd68c · outbound

This paper cites Guminov, A.

Mirror Descent Methods for Quasar Convex Optimization Problems With Non-Smooth Inequality Constraints Guminov, A

Reference 14

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Observation 602c670c-2ef8-445a-86a5-e1c3de565cb4 · outbound

This paper cites Hardt, T.

Mirror Descent Methods for Quasar Convex Optimization Problems With Non-Smooth Inequality Constraints Hardt, T

Reference 15

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Observation 1b2f1346-a2e9-4a98-bc53-91dbf4c312de · outbound

This paper cites Hermant, J.-F.

Mirror Descent Methods for Quasar Convex Optimization Problems With Non-Smooth Inequality Constraints Hermant, J.-F

Reference 16

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Observation 82a762bf-d606-4bfd-b9c2-20b8b13687a1 · outbound

This paper cites Hinder, A.

Mirror Descent Methods for Quasar Convex Optimization Problems With Non-Smooth Inequality Constraints Hinder, A

Reference 17

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Observation c18f0e7a-fdd8-4ede-a81e-c6c148edf438 · outbound

This paper cites On The Convergence of First Order Methods for Quasar-Convex Optimization.

Mirror Descent Methods for Quasar Convex Optimization Problems With Non-Smooth Inequality Constraints On The Convergence of First Order Methods for Quasar-Convex Optimization

Reference 18

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Observation f87828c3-4401-4468-97fd-aaf9bd71b980 · outbound

This paper cites Robust Learning Meets Quasar-Convex Optimization: Inexact High-Order Proximal-Point Methods.

Mirror Descent Methods for Quasar Convex Optimization Problems With Non-Smooth Inequality Constraints Robust Learning Meets Quasar-Convex Optimization: Inexact High-Order Proximal-Point Methods

Reference 19

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Observation 557aa5dc-ec0a-4134-85bb-c6b8e6cbc2f8 · outbound

This paper cites Accelerated Mirror Descent for Non-Euclidean Star-convex Functions.

Mirror Descent Methods for Quasar Convex Optimization Problems With Non-Smooth Inequality Constraints Accelerated Mirror Descent for Non-Euclidean Star-convex Functions

Reference 20

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Observation 76a12b20-e43f-45cc-80c3-b4d5ee2fc69d · outbound

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Mirror Descent Methods for Quasar Convex Optimization Problems With Non-Smooth Inequality Constraints Unresolved cited work

Reference 21

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Observation ee4b346d-751a-4d93-bcae-aad4e394e8c4 · outbound

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Mirror Descent Methods for Quasar Convex Optimization Problems With Non-Smooth Inequality Constraints Unresolved cited work

Reference 22

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Observation 8865e970-a83e-4b6f-9eef-3ade399d0b20 · outbound

This paper cites Smooth Quasar-Convex Optimization with Constraints.

Mirror Descent Methods for Quasar Convex Optimization Problems With Non-Smooth Inequality Constraints Smooth Quasar-Convex Optimization with Constraints

Reference 23

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Observation 7c565f14-b3f3-4b89-8d3e-d63f1d35912a · outbound

This paper cites Cubic regularization of Newton method and its global performance.

Mirror Descent Methods for Quasar Convex Optimization Problems With Non-Smooth Inequality Constraints Cubic regularization of Newton method and its global performance

Reference 24

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Observation dccc4191-9570-4333-b225-caf50b411898 · outbound

This paper cites Nemirovskii: Efficient methods for large-scale convex optimization problems.

Mirror Descent Methods for Quasar Convex Optimization Problems With Non-Smooth Inequality Constraints Nemirovskii: Efficient methods for large-scale convex optimization problems

Reference 25

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Observation bceb73f7-b9a0-45df-81e7-2e213fb62b3c · outbound

This paper cites Nemirovsky, D.

Mirror Descent Methods for Quasar Convex Optimization Problems With Non-Smooth Inequality Constraints Nemirovsky, D

Reference 26

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Observation 2cf024fb-f20e-4420-a9ec-7d7e3e6d7f5e · outbound

This paper cites Polyak: A general method of solving extremum problems.

Mirror Descent Methods for Quasar Convex Optimization Problems With Non-Smooth Inequality Constraints Polyak: A general method of solving extremum problems

Reference 27

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Observation 27faa470-34c1-45cc-bed1-400fc9da7a67 · outbound

This paper cites S., Alkousa, M.

Mirror Descent Methods for Quasar Convex Optimization Problems With Non-Smooth Inequality Constraints S., Alkousa, M

Reference 28

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Observation 8d190390-c224-4133-903b-8e5fd50cc094 · outbound

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Mirror Descent Methods for Quasar Convex Optimization Problems With Non-Smooth Inequality Constraints Unresolved cited work

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Observation f4dbce77-3e1f-4041-a93f-0612f3f714f4 · outbound

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Mirror Descent Methods for Quasar Convex Optimization Problems With Non-Smooth Inequality Constraints Unresolved cited work

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Observation 7a9a6421-45df-4457-b7f7-dcf1d11cc8bc · outbound

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Mirror Descent Methods for Quasar Convex Optimization Problems With Non-Smooth Inequality Constraints Unresolved cited work

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This paper cites Shpirko, Yu.

Mirror Descent Methods for Quasar Convex Optimization Problems With Non-Smooth Inequality Constraints Shpirko, Yu

Reference 32

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Mirror Descent Methods for Quasar Convex Optimization Problems With Non-Smooth Inequality Constraints Unresolved cited work

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Observation d9dde1fc-4cc4-498e-90fa-8f4c87b48e7e · outbound

This paper cites On some mirror descent methods for strongly convex programming problems with Lipschitz functional constraints.

Mirror Descent Methods for Quasar Convex Optimization Problems With Non-Smooth Inequality Constraints On some mirror descent methods for strongly convex programming problems with Lipschitz functional constraints

Reference 34

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Observation d68a78ff-a39f-43f5-80bd-d81448428c33 · outbound

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Mirror Descent Methods for Quasar Convex Optimization Problems With Non-Smooth Inequality Constraints Unresolved cited work

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Mirror Descent Methods for Quasar Convex Optimization Problems With Non-Smooth Inequality Constraints Unresolved cited work

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Observation fe96288e-511d-4268-bb0e-6379c4a9a9a0 · outbound

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Mirror Descent Methods for Quasar Convex Optimization Problems With Non-Smooth Inequality Constraints Unresolved cited work

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source=pdf_text observed=2026-08-02T14:05:55.514579Z digest=sha256:f9cbe205f97a285c2e7e5d5f6f5f276a10c9a4f68422d170d9c9f4c5b7c428c2

Observation 7a3d620c-41cd-4d3a-bcab-5bcfe596ea39 · outbound

This paper cites Continuized Acceleration for Quasar Convex Functions in Non-Convex Optimization.

Mirror Descent Methods for Quasar Convex Optimization Problems With Non-Smooth Inequality Constraints Continuized Acceleration for Quasar Convex Functions in Non-Convex Optimization

Reference 38

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source=pdf_text observed=2026-08-02T14:05:55.609883Z digest=sha256:1fc3a49af70d073bdb32aa71c2efd950a2cf524b5080db834171fffacf041efa

Observation ddc0fc73-c235-4be9-b359-fd7f2d3fc298 · outbound

This paper cites Xu: Primal-dual stochastic gradient method for convex programs with many func- tional constraints.

Mirror Descent Methods for Quasar Convex Optimization Problems With Non-Smooth Inequality Constraints Xu: Primal-dual stochastic gradient method for convex programs with many func- tional constraints

Reference 39

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source=pdf_text observed=2026-08-02T14:05:55.721700Z digest=sha256:a661ab635e4cb0d30526006a0765d5228a4ae4d16a06109f085258c0762abf40

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