Paper Citation Record · LEDGER

An Efficient Stochastic First-Order Algorithm for Nonconvex--Strongly Concave Minimax Optimization beyond Lipschitz Smoothness

As of 11 August 2026, this Paper Citation Record lists 44 of 44 outbound references and 0 inbound Pith citation observations for arXiv:2603.04940.

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2603.04940 v2

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measured 44 of 44 reference resolution

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44 of 44 outbound references displayed

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Outbound references

Observation 6ace8078-1ed4-409e-aea9-9f9e2d1cda6a · outbound

This paper cites Duchi, Dylan J.

An Efficient Stochastic First-Order Algorithm for Nonconvex--Strongly Concave Minimax Optimization beyond Lipschitz Smoothness Duchi, Dylan J

Reference 1

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Observation caa2f337-9d39-498a-b9d7-f5e49af82c75 · outbound

This paper cites Alternating proximal-gra dient steps for (stochastic) nonconvex-concave minimax problems.

An Efficient Stochastic First-Order Algorithm for Nonconvex--Strongly Concave Minimax Optimization beyond Lipschitz Smoothness Alternating proximal-gra dient steps for (stochastic) nonconvex-concave minimax problems

Reference 2

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Observation e5510f19-65b1-4cc8-be7f-aadf30dcd529 · outbound

This paper cites An eﬃcient stochastic algorithm for decentralized nonconvex-strongly-concave minimax optimization.

An Efficient Stochastic First-Order Algorithm for Nonconvex--Strongly Concave Minimax Optimization beyond Lipschitz Smoothness An eﬃcient stochastic algorithm for decentralized nonconvex-strongly-concave minimax optimization

Reference 3

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Observation 66a4052b-059e-43c9-9b72-99c0ec9371b5 · outbound

This paper cites Genera lized-smooth nonconvex optimization is as eﬃcient as smooth nonconvex optimizatio n.

An Efficient Stochastic First-Order Algorithm for Nonconvex--Strongly Concave Minimax Optimization beyond Lipschitz Smoothness Genera lized-smooth nonconvex optimization is as eﬃcient as smooth nonconvex optimizatio n

Reference 4

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Observation 18a1f584-474a-41be-82a3-17e1879f68fc · outbound

This paper cites Robustness to unbounded smoothness of generalized signSGD.

An Efficient Stochastic First-Order Algorithm for Nonconvex--Strongly Concave Minimax Optimization beyond Lipschitz Smoothness Robustness to unbounded smoothness of generalized signSGD

Reference 5

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This paper cites an unresolved cited work.

An Efficient Stochastic First-Order Algorithm for Nonconvex--Strongly Concave Minimax Optimization beyond Lipschitz Smoothness Unresolved cited work

Reference 6

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Observation 71c8b5bb-0903-44d8-9433-ad7e19d28af2 · outbound

This paper cites Momentum improves norma lized sgd.

An Efficient Stochastic First-Order Algorithm for Nonconvex--Strongly Concave Minimax Optimization beyond Lipschitz Smoothness Momentum improves norma lized sgd

Reference 7

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Observation d60d6a9f-97f7-47f5-aa4d-e7f644941ecd · outbound

This paper cites Stochastic optimization under distributional drift.

An Efficient Stochastic First-Order Algorithm for Nonconvex--Strongly Concave Minimax Optimization beyond Lipschitz Smoothness Stochastic optimization under distributional drift

Reference 8

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Observation e8164fa5-6f98-4ab8-923f-db6c797a999a · outbound

This paper cites Beyond uniform smoothness: A stopped analysis of adaptive sgd.

An Efficient Stochastic First-Order Algorithm for Nonconvex--Strongly Concave Minimax Optimization beyond Lipschitz Smoothness Beyond uniform smoothness: A stopped analysis of adaptive sgd

Reference 9

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Observation 57543c70-be62-4be8-9693-e03063b4e457 · outbound

This paper cites Goodfellow, Jean Pouget-Abadie, Mehdi Mirza, Bing Xu, David Warde-Farley, Sherjil Ozair, Aaron Courville, and Yoshua Bengio.

An Efficient Stochastic First-Order Algorithm for Nonconvex--Strongly Concave Minimax Optimization beyond Lipschitz Smoothness Goodfellow, Jean Pouget-Abadie, Mehdi Mirza, Bing Xu, David Warde-Farley, Sherjil Ozair, Aaron Courville, and Yoshua Bengio

Reference 10

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Observation d3341b32-7b9b-4ac4-a206-91e8073c7be4 · outbound

This paper cites Long short-term memory.

An Efficient Stochastic First-Order Algorithm for Nonconvex--Strongly Concave Minimax Optimization beyond Lipschitz Smoothness Long short-term memory

Reference 11

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Observation 35775c5c-c4a9-4ee4-bcc7-284a39b5575a · outbound

This paper cites Ac celerated zeroth-order and ﬁrst-order momentum methods from mini to minimax optimizat ion.

An Efficient Stochastic First-Order Algorithm for Nonconvex--Strongly Concave Minimax Optimization beyond Lipschitz Smoothness Ac celerated zeroth-order and ﬁrst-order momentum methods from mini to minimax optimizat ion

Reference 12

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Observation a1e3c44c-2ab3-4872-9b74-e0709c495411 · outbound

This paper cites Adagda: Faste r adaptive gradient descent ascent methods for minimax optimization.

An Efficient Stochastic First-Order Algorithm for Nonconvex--Strongly Concave Minimax Optimization beyond Lipschitz Smoothness Adagda: Faste r adaptive gradient descent ascent methods for minimax optimization

Reference 13

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Observation 573f1598-3af2-43af-bafe-361e525fddaa · outbound

This paper cites Parameter-agnostic optimization un- der relaxed smoothness.

An Efficient Stochastic First-Order Algorithm for Nonconvex--Strongly Concave Minimax Optimization beyond Lipschitz Smoothness Parameter-agnostic optimization un- der relaxed smoothness

Reference 14

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Observation f94ba06f-7da6-455f-b7d6-1bba66c7dd80 · outbound

This paper cites A Short Note on Concentration Inequalities for Random Vectors with SubGaussian Norm.

An Efficient Stochastic First-Order Algorithm for Nonconvex--Strongly Concave Minimax Optimization beyond Lipschitz Smoothness A Short Note on Concentration Inequalities for Random Vectors with SubGaussian Norm

Reference 15

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Observation b5a0be0a-82a6-4d17-a4c9-3d804515867c · outbound

This paper cites N on-convex distributionally robust optimization: Non-asymptotic analysis.

An Efficient Stochastic First-Order Algorithm for Nonconvex--Strongly Concave Minimax Optimization beyond Lipschitz Smoothness N on-convex distributionally robust optimization: Non-asymptotic analysis

Reference 16

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Observation 7fc8b1bc-b870-4c52-aaa4-b84a377b9287 · outbound

This paper cites Large-scale methods for dis- tributionally robust optimization.

An Efficient Stochastic First-Order Algorithm for Nonconvex--Strongly Concave Minimax Optimization beyond Lipschitz Smoothness Large-scale methods for dis- tributionally robust optimization

Reference 17

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Observation b778f5c9-d52b-4d79-8f85-1e1f950ffb9a · outbound

This paper cites Convex and non-convex optimization under generalized smoothness.

An Efficient Stochastic First-Order Algorithm for Nonconvex--Strongly Concave Minimax Optimization beyond Lipschitz Smoothness Convex and non-convex optimization under generalized smoothness

Reference 18

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Observation 3070e8a6-38ec-4315-a775-6be6a81b08a0 · outbound

This paper cites Con vergence of adam under relaxed assumptions.

An Efficient Stochastic First-Order Algorithm for Nonconvex--Strongly Concave Minimax Optimization beyond Lipschitz Smoothness Con vergence of adam under relaxed assumptions

Reference 19

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Observation 09208392-7df5-4438-a58a-948dfcc2c5e3 · outbound

This paper cites Tiada: A time-scale a daptive algorithm for nonconvex minimax optimization.

An Efficient Stochastic First-Order Algorithm for Nonconvex--Strongly Concave Minimax Optimization beyond Lipschitz Smoothness Tiada: A time-scale a daptive algorithm for nonconvex minimax optimization

Reference 20

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Observation c1296c2a-6a37-4c19-9a84-1f9258f24df7 · outbound

This paper cites On gradient descent ascent for nonconvex-concave minimax problems.

An Efficient Stochastic First-Order Algorithm for Nonconvex--Strongly Concave Minimax Optimization beyond Lipschitz Smoothness On gradient descent ascent for nonconvex-concave minimax problems

Reference 21

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Observation 485ee688-b87b-4323-b462-ac44b0fa8d2a · outbound

This paper cites Near-Optimal Non-Convex Stochastic Optimization under Generalized Smoothness.

An Efficient Stochastic First-Order Algorithm for Nonconvex--Strongly Concave Minimax Optimization beyond Lipschitz Smoothness Near-Optimal Non-Convex Stochastic Optimization under Generalized Smoothness

Reference 22

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Observation a353d7b5-4670-4792-96fd-745b3026ee9a · outbound

This paper cites Stoc hastic recursive gradient descent ascent for stochastic nonconvex-strongly-concave minimax problems.

An Efficient Stochastic First-Order Algorithm for Nonconvex--Strongly Concave Minimax Optimization beyond Lipschitz Smoothness Stoc hastic recursive gradient descent ascent for stochastic nonconvex-strongly-concave minimax problems

Reference 23

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This paper cites Tight analysis of extra-gradient and optimistic gradient methods for nonc onvex minimax problems.

An Efficient Stochastic First-Order Algorithm for Nonconvex--Strongly Concave Minimax Optimization beyond Lipschitz Smoothness Tight analysis of extra-gradient and optimistic gradient methods for nonc onvex minimax problems

Reference 24

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An Efficient Stochastic First-Order Algorithm for Nonconvex--Strongly Concave Minimax Optimization beyond Lipschitz Smoothness Unresolved cited work

Reference 25

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Observation 3345060f-5907-4dcc-9d7b-a37a2a7684b2 · outbound

This paper cites Weakly-convex–concave min– max optimization: provable algorithms and applications in machine learning.

An Efficient Stochastic First-Order Algorithm for Nonconvex--Strongly Concave Minimax Optimization beyond Lipschitz Smoothness Weakly-convex–concave min– max optimization: provable algorithms and applications in machine learning

Reference 26

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Observation c712cdea-021f-405a-958d-d2f40ddbdc2b · outbound

This paper cites Variance-reduced clipping for non-convex optimization.

An Efficient Stochastic First-Order Algorithm for Nonconvex--Strongly Concave Minimax Optimization beyond Lipschitz Smoothness Variance-reduced clipping for non-convex optimization

Reference 27

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Observation c18cf2e8-4163-462c-9fe2-fb64192496c4 · outbound

This paper cites Federated minimax optimization: Improved convergence analyses and algorith ms.

An Efficient Stochastic First-Order Algorithm for Nonconvex--Strongly Concave Minimax Optimization beyond Lipschitz Smoothness Federated minimax optimization: Improved convergence analyses and algorith ms

Reference 28

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Observation 2efd21ef-6773-4671-8426-e4ad1db56974 · outbound

This paper cites Certiﬁa ble distributional robustness with principled adversarial training.

An Efficient Stochastic First-Order Algorithm for Nonconvex--Strongly Concave Minimax Optimization beyond Lipschitz Smoothness Certiﬁa ble distributional robustness with principled adversarial training

Reference 29

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This paper cites Mome ntum ensures convergence of signsgd under weaker assumptions.

An Efficient Stochastic First-Order Algorithm for Nonconvex--Strongly Concave Minimax Optimization beyond Lipschitz Smoothness Mome ntum ensures convergence of signsgd under weaker assumptions

Reference 30

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Observation 87a76c4a-1162-4af1-9c54-c5a181d543e9 · outbound

This paper cites Theoretical ana lysis of adversarial learning: A minimax approach.

An Efficient Stochastic First-Order Algorithm for Nonconvex--Strongly Concave Minimax Optimization beyond Lipschitz Smoothness Theoretical ana lysis of adversarial learning: A minimax approach

Reference 31

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Observation 237b0748-7994-4ccb-90fc-6673fe8a762f · outbound

This paper cites Co nvergence of adagrad for non-convex objectives: Simple proofs and relaxed assumpti ons.

An Efficient Stochastic First-Order Algorithm for Nonconvex--Strongly Concave Minimax Optimization beyond Lipschitz Smoothness Co nvergence of adagrad for non-convex objectives: Simple proofs and relaxed assumpti ons

Reference 32

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Observation 96c07a68-7f5e-43d8-8bc8-caf93adffe81 · outbound

This paper cites Solving a class of non-convex minimax optimization in federated lear ning.

An Efficient Stochastic First-Order Algorithm for Nonconvex--Strongly Concave Minimax Optimization beyond Lipschitz Smoothness Solving a class of non-convex minimax optimization in federated lear ning

Reference 33

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Observation 0d41dfd5-02bb-48b0-a217-bdd640cc4c3e · outbound

This paper cites Delving into the convergence of generalized smooth minimax optimization.

An Efficient Stochastic First-Order Algorithm for Nonconvex--Strongly Concave Minimax Optimization beyond Lipschitz Smoothness Delving into the convergence of generalized smooth minimax optimization

Reference 34

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Observation 59be80d6-7009-4a07-a8de-11f1cb86354c · outbound

This paper cites A stochastic gda method with backtracking for solving nonconvex (strongly) concave minimax problems, 2024.

An Efficient Stochastic First-Order Algorithm for Nonconvex--Strongly Concave Minimax Optimization beyond Lipschitz Smoothness A stochastic gda method with backtracking for solving nonconvex (strongly) concave minimax problems, 2024

Reference 35

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This paper cites Vincent Poor.

An Efficient Stochastic First-Order Algorithm for Nonconvex--Strongly Concave Minimax Optimization beyond Lipschitz Smoothness Vincent Poor

Reference 36

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Observation 7e9f76df-d641-467c-afed-5b70b2af225f · outbound

This paper cites Nest your adaptive al gorithm for parameter-agnostic nonconvex minimax optimization.

An Efficient Stochastic First-Order Algorithm for Nonconvex--Strongly Concave Minimax Optimization beyond Lipschitz Smoothness Nest your adaptive al gorithm for parameter-agnostic nonconvex minimax optimization

Reference 37

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Observation 21b3340b-141b-4aac-851d-cd2eadc77469 · outbound

This paper cites Faster single-loop algo- rithms for minimax optimization without strong concavity.

An Efficient Stochastic First-Order Algorithm for Nonconvex--Strongly Concave Minimax Optimization beyond Lipschitz Smoothness Faster single-loop algo- rithms for minimax optimization without strong concavity

Reference 38

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Observation 0567047a-827e-42c1-91d1-a9c9969e6286 · outbound

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An Efficient Stochastic First-Order Algorithm for Nonconvex--Strongly Concave Minimax Optimization beyond Lipschitz Smoothness Impr oved analysis of clipping algo- rithms for non-convex optimization

Reference 39

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Observation 883e9134-c96f-43c8-b2db-7e57b4b90c0a · outbound

This paper cites Why gradient clipping accel- erates training: A theoretical justiﬁcation for adaptivit y.

An Efficient Stochastic First-Order Algorithm for Nonconvex--Strongly Concave Minimax Optimization beyond Lipschitz Smoothness Why gradient clipping accel- erates training: A theoretical justiﬁcation for adaptivit y

Reference 40

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Observation c226fc11-e701-442d-a730-f29e56abf253 · outbound

This paper cites Sapd+: An accelerated stochastic method for nonconvex-concave minimax problems.

An Efficient Stochastic First-Order Algorithm for Nonconvex--Strongly Concave Minimax Optimization beyond Lipschitz Smoothness Sapd+: An accelerated stochastic method for nonconvex-concave minimax problems

Reference 41

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Observation db5cbf90-fb2e-47c2-8b9f-bf3a343f9154 · outbound

This paper cites Finding second-order stationary points for generalized-smooth nonconvex minimax optimization via gradient-based algorithm, 2025.

An Efficient Stochastic First-Order Algorithm for Nonconvex--Strongly Concave Minimax Optimization beyond Lipschitz Smoothness Finding second-order stationary points for generalized-smooth nonconvex minimax optimization via gradient-based algorithm, 2025

Reference 42

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Observation c11c32b7-316f-409e-a0a2-27531a57c037 · outbound

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An Efficient Stochastic First-Order Algorithm for Nonconvex--Strongly Concave Minimax Optimization beyond Lipschitz Smoothness Unresolved cited work

Reference 43

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An Efficient Stochastic First-Order Algorithm for Nonconvex--Strongly Concave Minimax Optimization beyond Lipschitz Smoothness Unresolved cited work

Reference 44

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