Paper Citation Record · LEDGER

Lower Bounds for Linear Minimization Oracle Methods Optimizing over Strongly Convex Sets

As of 19 August 2026, this Paper Citation Record lists 29 of 29 outbound references and 2 inbound Pith citation observations for arXiv:2602.22608.

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

pith.paper-citation-record.v1
2602.22608 v2

Coverage vector

measured 29 of 29 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-02T20:54:16.401959Z

measured 31 of 31 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-19T06:32:44.657259+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-05-22T04:22:05.402926Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-22T04:24:35.404663Z

Reference resolution

29 of 29 outbound references displayed

verified exact0
verified fuzzy0
unresolved29
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation d8dee3c2-d3c0-412b-9e79-d24efb3a9c46 · outbound

This paper cites Faster rates for the Frank-Wolfe method over strongly-convex sets.

Lower Bounds for Linear Minimization Oracle Methods Optimizing over Strongly Convex Sets Faster rates for the Frank-Wolfe method over strongly-convex sets

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-02T20:54:13.930005Z

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Observation d36aed1e-601b-4ccf-ac2d-5efc346a990e · outbound

This paper cites Combettes, Hamed Hassani, Amin Karbasi, Aryan Mokhtari, and Sebastian Pokutta.Conditional gradient methods: From core principles to AI applications.

Lower Bounds for Linear Minimization Oracle Methods Optimizing over Strongly Convex Sets Combettes, Hamed Hassani, Amin Karbasi, Aryan Mokhtari, and Sebastian Pokutta.Conditional gradient methods: From core principles to AI applications

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-02T20:54:14.013136Z

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Observation 9c6297e7-6bba-4cb2-8836-874a954b3b4f · outbound

This paper cites Strong convexity of sets and functions.Journal of Mathematical Economics, 9(1-2):187–205, 1982.

Lower Bounds for Linear Minimization Oracle Methods Optimizing over Strongly Convex Sets Strong convexity of sets and functions.Journal of Mathematical Economics, 9(1-2):187–205, 1982

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-02T20:54:14.085523Z

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Observation e9fcc2f5-03aa-47b6-8610-7202eda7f380 · outbound

This paper cites Gauges and accelerated optimization over smooth and/or strongly convex sets, 2023.

Lower Bounds for Linear Minimization Oracle Methods Optimizing over Strongly Convex Sets Gauges and accelerated optimization over smooth and/or strongly convex sets, 2023

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-02T20:54:14.174782Z

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Observation 8a2e9c80-833f-445a-bd2b-352ebf33aba1 · outbound

This paper cites On the global linear convergence of Frank-Wolfe optimization variants.Advances in neural information processing systems, 28, 2015.

Lower Bounds for Linear Minimization Oracle Methods Optimizing over Strongly Convex Sets On the global linear convergence of Frank-Wolfe optimization variants.Advances in neural information processing systems, 28, 2015

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-02T20:54:14.258833Z

Source-reported events for the cited work

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Observation e7b67b21-8e77-499d-aea7-b52595a253af · outbound

This paper cites Linearly convergent away-step conditional gradient for non-strongly convex functions.Mathematical Programming, 164(1):1–27, 2017.

Lower Bounds for Linear Minimization Oracle Methods Optimizing over Strongly Convex Sets Linearly convergent away-step conditional gradient for non-strongly convex functions.Mathematical Programming, 164(1):1–27, 2017

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-02T20:54:14.370185Z

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Observation 317cbcce-9207-4016-b214-f2507396b8c5 · outbound

This paper cites Pairwise conditional gradients without swap steps and sparser kernel herding.

Lower Bounds for Linear Minimization Oracle Methods Optimizing over Strongly Convex Sets Pairwise conditional gradients without swap steps and sparser kernel herding

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-02T20:54:14.471893Z

Source-reported events for the cited work

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Observation 5db4e90d-093c-4052-9045-4d632900f248 · outbound

This paper cites An extension of the Frank and Wolfe method of feasible directions.Mathematical Programming, 6(1):14–27, 1974.

Lower Bounds for Linear Minimization Oracle Methods Optimizing over Strongly Convex Sets An extension of the Frank and Wolfe method of feasible directions.Mathematical Programming, 6(1):14–27, 1974

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-02T20:54:14.541297Z

Source-reported events for the cited work

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Observation a78067b9-9fbf-4134-9e47-072d0207b0ea · outbound

This paper cites Blended conditional gradients.

Lower Bounds for Linear Minimization Oracle Methods Optimizing over Strongly Convex Sets Blended conditional gradients

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-02T20:54:14.595759Z

Source-reported events for the cited work

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Observation 3f2bb55d-d024-405a-8f2c-40fcd2e66b11 · outbound

This paper cites An algorithm for quadratic programming.Naval research logistics quarterly, 3(1-2):95–110, 1956.

Lower Bounds for Linear Minimization Oracle Methods Optimizing over Strongly Convex Sets An algorithm for quadratic programming.Naval research logistics quarterly, 3(1-2):95–110, 1956

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-02T20:54:14.679315Z

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Observation 05ea03db-1653-4407-8497-a2cdf3a45866 · outbound

This paper cites Revisiting Frank-Wolfe: Projection-free sparse convex optimization.

Lower Bounds for Linear Minimization Oracle Methods Optimizing over Strongly Convex Sets Revisiting Frank-Wolfe: Projection-free sparse convex optimization

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-02T20:54:14.793084Z

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Unavailable: canonical work link unavailable.

Observation 739e71b5-061a-4684-92b7-1f9ce288d2a0 · outbound

This paper cites The complexity of large-scale convex programming under a linear optimization oracle,.

Lower Bounds for Linear Minimization Oracle Methods Optimizing over Strongly Convex Sets The complexity of large-scale convex programming under a linear optimization oracle,

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-02T20:54:14.859475Z

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Observation fbede5de-13da-4bda-8854-a54beca3658f · outbound

This paper cites Lower Bounds for Frank-Wolfe on Strongly Convex Sets.

Lower Bounds for Linear Minimization Oracle Methods Optimizing over Strongly Convex Sets Lower Bounds for Frank-Wolfe on Strongly Convex Sets

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-02T20:54:14.916202Z

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Observation 471ecd9e-9d98-475a-a5ef-b6ed1dc4ab95 · outbound

This paper cites Wiley-Interscience Series in Discrete Mathematics.

Lower Bounds for Linear Minimization Oracle Methods Optimizing over Strongly Convex Sets Wiley-Interscience Series in Discrete Mathematics

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-02T20:54:15.041398Z

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Observation 47b54ac1-2406-4bef-ad4b-18b749f84d30 · outbound

This paper cites Performance of first-order methods for smooth convex minimization: a novel approach.Mathematical Programming, 145(1):451–482, 2014.

Lower Bounds for Linear Minimization Oracle Methods Optimizing over Strongly Convex Sets Performance of first-order methods for smooth convex minimization: a novel approach.Mathematical Programming, 145(1):451–482, 2014

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-02T20:54:15.170766Z

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Observation 07209d1a-2625-4d88-9c4e-dd3cf133cef7 · outbound

This paper cites Smooth strongly convex interpolation and exact worst-case performance of first-order methods.Mathematical Programming, 161:307–345, 2017.

Lower Bounds for Linear Minimization Oracle Methods Optimizing over Strongly Convex Sets Smooth strongly convex interpolation and exact worst-case performance of first-order methods.Mathematical Programming, 161:307–345, 2017

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-02T20:54:15.226556Z

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Observation 82cf32f5-ab38-4155-a0e3-5bb9813bd1f6 · outbound

This paper cites Exact worst-case performance of first-order methods for composite convex optimization.SIAM Journal on Optimization, 27(3):1283–1313, 2017.

Lower Bounds for Linear Minimization Oracle Methods Optimizing over Strongly Convex Sets Exact worst-case performance of first-order methods for composite convex optimization.SIAM Journal on Optimization, 27(3):1283–1313, 2017

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-02T20:54:15.301126Z

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Observation a80aa2c4-7898-4bdb-9502-bab6852d8e06 · outbound

This paper cites Optimized first-order methods for smooth convex minimization.

Lower Bounds for Linear Minimization Oracle Methods Optimizing over Strongly Convex Sets Optimized first-order methods for smooth convex minimization

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-02T20:54:15.371394Z

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Observation 42e5b682-9f14-4d73-96b4-911ccc9e5fc4 · outbound

This paper cites The exact information-based complexity of smooth convex minimization.Journal of Complexity, 39:1–16, 2017.

Lower Bounds for Linear Minimization Oracle Methods Optimizing over Strongly Convex Sets The exact information-based complexity of smooth convex minimization.Journal of Complexity, 39:1–16, 2017

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-02T20:54:15.467766Z

Source-reported events for the cited work

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Observation f6c80078-b47b-452b-a0ef-7f574673ab4c · outbound

This paper cites Performance Estimation for Smooth and Strongly Convex Sets.

Lower Bounds for Linear Minimization Oracle Methods Optimizing over Strongly Convex Sets Performance Estimation for Smooth and Strongly Convex Sets

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-02T20:54:15.532939Z

Source-reported events for the cited work

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Observation 45ea1120-1a70-41b2-a379-827b98ab6419 · outbound

This paper cites an unresolved cited work.

Lower Bounds for Linear Minimization Oracle Methods Optimizing over Strongly Convex Sets Unresolved cited work

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-02T20:54:15.580450Z

Source-reported events for the cited work

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Observation c57d9d19-820c-461b-99ad-bd74ed33588d · outbound

This paper cites Accelerated affine-invariant convergence rates of the Frank–Wolfe algorithm with open-loop step-sizes.Mathematical Programming, 214(1–2):201–245, 2025.

Lower Bounds for Linear Minimization Oracle Methods Optimizing over Strongly Convex Sets Accelerated affine-invariant convergence rates of the Frank–Wolfe algorithm with open-loop step-sizes.Mathematical Programming, 214(1–2):201–245, 2025

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-02T20:54:15.678295Z

Source-reported events for the cited work

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Observation 1e54f890-160a-446b-afc7-849a37e2a98d · outbound

This paper cites Fast convergence of Frank-Wolfe algorithms on polytopes.Mathematics of Operations Research, 2025.

Lower Bounds for Linear Minimization Oracle Methods Optimizing over Strongly Convex Sets Fast convergence of Frank-Wolfe algorithms on polytopes.Mathematics of Operations Research, 2025

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-02T20:54:15.767364Z

Source-reported events for the cited work

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Observation a52fa30f-2d29-4fa1-aa6c-b54d43aac9aa · outbound

This paper cites Efficient.

Lower Bounds for Linear Minimization Oracle Methods Optimizing over Strongly Convex Sets Efficient

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-02T20:54:15.813131Z

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Observation df27f66d-21de-4752-ab77-25176044874b · outbound

This paper cites Radial duality part i: foundations.Mathematical Programming, 205(1–2):33–68, 2024.

Lower Bounds for Linear Minimization Oracle Methods Optimizing over Strongly Convex Sets Radial duality part i: foundations.Mathematical Programming, 205(1–2):33–68, 2024

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-02T20:54:15.887330Z

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Observation 61f704f1-4737-4812-9d56-4e8816fda962 · outbound

This paper cites Radial duality part ii: applications and algorithms.Mathematical Programming, 205(1–2):69–105, 2023.

Lower Bounds for Linear Minimization Oracle Methods Optimizing over Strongly Convex Sets Radial duality part ii: applications and algorithms.Mathematical Programming, 205(1–2):69–105, 2023

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-02T20:54:15.939548Z

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Observation 1c3ea8da-cf99-4df1-98e9-9f0a02cc090b · outbound

This paper cites Efficient projection-free online convex optimization with membership oracle.

Lower Bounds for Linear Minimization Oracle Methods Optimizing over Strongly Convex Sets Efficient projection-free online convex optimization with membership oracle

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-02T20:54:16.088566Z

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Observation 4cfb1910-3582-4800-908a-d92e389d1298 · outbound

This paper cites Projection-free adaptive regret with membership oracles.

Lower Bounds for Linear Minimization Oracle Methods Optimizing over Strongly Convex Sets Projection-free adaptive regret with membership oracles

Reference 28

Resolution: unresolved; no resolver link, observed 2026-08-02T20:54:16.221936Z

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Observation 719b0960-98e8-4494-9996-eb6172484432 · outbound

This paper cites Scalable Projection-Free Optimization Methods via MultiRadial Duality Theory.

Lower Bounds for Linear Minimization Oracle Methods Optimizing over Strongly Convex Sets Scalable Projection-Free Optimization Methods via MultiRadial Duality Theory

Reference 29

Resolution: unresolved; no resolver link, observed 2026-08-02T20:54:16.401959Z

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Pith citing papers

Observation c8e5c149-2789-4f62-a309-806e0f36d9db · inbound

Local LMO: Constrained Gradient Optimization via a Local Linear Minimization Oracle cites this paper.

Local LMO: Constrained Gradient Optimization via a Local Linear Minimization Oracle Lower Bounds for Linear Minimization Oracle Methods Optimizing over Strongly Convex Sets

Reference 44

Resolution: metadata mismatch; arxiv_id, observed 2026-07-15T02:22:01.225620Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 8a86808c-2533-4488-845c-1642e7f93a86 · inbound

A conditional-gradient-based single-loop augmented Lagrangian method for inequality constrained optimization cites this paper.

A conditional-gradient-based single-loop augmented Lagrangian method for inequality constrained optimization Lower Bounds for Linear Minimization Oracle Methods Optimizing over Strongly Convex Sets

Reference 30

Resolution: verified exact; arxiv_id, observed 2026-07-15T02:22:01.225620Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.