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Paper Citation Record · LEDGER

Solving Zero-Sum Games with Fewer Matrix-Vector Products

As of 16 August 2026, this Paper Citation Record lists 52 of 52 outbound references and 0 inbound Pith citation observations for arXiv:2509.04426.

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pith.paper-citation-record.v1
2509.04426 v2

Coverage vector

measured 52 of 52 reference resolution

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measured 52 of 52 standing notices

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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

52 of 52 outbound references displayed

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External citation measurements

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Outbound references

Observation 8185e5f9-3ba1-4068-acdb-59c4a76516a1 · outbound

This paper cites Optimal Methods for Higher-Order Smooth Monotone Variational Inequalities.

Solving Zero-Sum Games with Fewer Matrix-Vector Products Optimal Methods for Higher-Order Smooth Monotone Variational Inequalities

Reference 1

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Observation 1cfec7b8-08fd-48a3-8b67-10d8f6ccbc6e · outbound

This paper cites Stochastic bias-reduced gradi- ent methods.

Solving Zero-Sum Games with Fewer Matrix-Vector Products Stochastic bias-reduced gradi- ent methods

Reference 2

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This paper cites Bailey and Georgios Piliouras.

Solving Zero-Sum Games with Fewer Matrix-Vector Products Bailey and Georgios Piliouras

Reference 3

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This paper cites Low-rank approximation with matrix- vector products.

Solving Zero-Sum Games with Fewer Matrix-Vector Products Low-rank approximation with matrix- vector products

Reference 4

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Observation e1c5bad0-8cb8-40d0-a170-cb5bc5528750 · outbound

This paper cites The gradient complexity of linear regression.

Solving Zero-Sum Games with Fewer Matrix-Vector Products The gradient complexity of linear regression

Reference 5

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Observation 271ddd10-cef2-4dc0-87e7-0dbaf0f8e8b9 · outbound

This paper cites Complexity of highly parallel non-smooth convex optimization.

Solving Zero-Sum Games with Fewer Matrix-Vector Products Complexity of highly parallel non-smooth convex optimization

Reference 6

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Observation 88f12b61-4bed-4f29-be88-46042d934fdf · outbound

This paper cites Near-optimal method for highly smooth convex optimization.

Solving Zero-Sum Games with Fewer Matrix-Vector Products Near-optimal method for highly smooth convex optimization

Reference 7

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Observation 4fb91cd6-f053-44ae-8abd-433853120ee4 · outbound

This paper cites Distributionally Robust Optimization via Ball Oracle Acceleration.

Solving Zero-Sum Games with Fewer Matrix-Vector Products Distributionally Robust Optimization via Ball Oracle Acceleration

Reference 8

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Observation cdfd7706-34da-4c2c-bb50-68089ab23ae2 · outbound

This paper cites Convex until proven guilty: dimension- free acceleration of gradient descent on non-convex functions.

Solving Zero-Sum Games with Fewer Matrix-Vector Products Convex until proven guilty: dimension- free acceleration of gradient descent on non-convex functions

Reference 9

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Observation 1498986f-d9ca-4600-ba25-5ab6eba43325 · outbound

This paper cites Variance reduction for matrix games.

Solving Zero-Sum Games with Fewer Matrix-Vector Products Variance reduction for matrix games

Reference 10

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Observation 2b195ad0-c53e-4d64-9177-b5d227456c87 · outbound

This paper cites Acceleration with a ball optimization oracle.

Solving Zero-Sum Games with Fewer Matrix-Vector Products Acceleration with a ball optimization oracle

Reference 11

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Observation 616ca0bf-6c71-4498-ada4-28baf51e8677 · outbound

This paper cites Coordinate methods for matrix games.

Solving Zero-Sum Games with Fewer Matrix-Vector Products Coordinate methods for matrix games

Reference 12

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Observation c09be62c-c4db-4758-ba04-1cc9f3d19849 · outbound

This paper cites Thinking inside the ball: Near-optimal minimization of the maximal loss.

Solving Zero-Sum Games with Fewer Matrix-Vector Products Thinking inside the ball: Near-optimal minimization of the maximal loss

Reference 13

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This paper cites Optimal and adap- tive monteiro-svaiter acceleration.

Solving Zero-Sum Games with Fewer Matrix-Vector Products Optimal and adap- tive monteiro-svaiter acceleration

Reference 14

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Observation 387b12bc-fafa-4cab-8032-e8e6aaa6b20c · outbound

This paper cites Resqueing parallel and private stochastic convex optimization.

Solving Zero-Sum Games with Fewer Matrix-Vector Products Resqueing parallel and private stochastic convex optimization

Reference 15

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Observation debe3548-751e-481a-97e8-058ba90f7162 · outbound

This paper cites A whole new ball game: A primal accelerated method for matrix games and minimizing the maximum of smooth functions.

Solving Zero-Sum Games with Fewer Matrix-Vector Products A whole new ball game: A primal accelerated method for matrix games and minimizing the maximum of smooth functions

Reference 16

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Observation 67ba49dc-a726-48e8-83f4-127cf96a18f2 · outbound

This paper cites Sublinear optimization for machine learning.

Solving Zero-Sum Games with Fewer Matrix-Vector Products Sublinear optimization for machine learning

Reference 17

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Observation 0cbf91b3-a462-4ee8-ac3c-9c217f05d09f · outbound

This paper cites Relative lipschitzness in extragradient methods and a direct recipe for acceleration.

Solving Zero-Sum Games with Fewer Matrix-Vector Products Relative lipschitzness in extragradient methods and a direct recipe for acceleration

Reference 18

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Source-reported events for the cited work

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Observation c051648e-bd92-4e9e-89ad-09a9a39b53c6 · outbound

This paper cites Near-optimal no-regret algorithms for zero-sum games.

Solving Zero-Sum Games with Fewer Matrix-Vector Products Near-optimal no-regret algorithms for zero-sum games

Reference 19

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Observation 95d947ff-b67a-4d55-a507-e440033b089c · outbound

This paper cites Composite objective mirror descent.

Solving Zero-Sum Games with Fewer Matrix-Vector Products Composite objective mirror descent

Reference 20

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Observation 1d58cd0f-73b7-4426-a619-9d1539e9e79d · outbound

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Solving Zero-Sum Games with Fewer Matrix-Vector Products Adaptive game playing using multiplicative weights

Reference 21

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Observation e09b317c-a577-4ca4-86dc-829a21ad1478 · outbound

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Solving Zero-Sum Games with Fewer Matrix-Vector Products Generative adversarial nets

Reference 22

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Source-reported events for the cited work

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Observation 9699e90f-b920-4855-adab-9900f91bfe1e · outbound

This paper cites A sublinear-time randomized approximation algorithm for matrix games.

Solving Zero-Sum Games with Fewer Matrix-Vector Products A sublinear-time randomized approximation algorithm for matrix games

Reference 23

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Observation ab7a0fb6-ef03-4b1e-bbeb-edddab212a4d · outbound

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Solving Zero-Sum Games with Fewer Matrix-Vector Products On lower complexity bounds for large-scale smooth convex optimization

Reference 24

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This paper cites Towards characterizing the first-order query complexity of learning (approximate) nash equilibria in zero-sum matrix games.

Solving Zero-Sum Games with Fewer Matrix-Vector Products Towards characterizing the first-order query complexity of learning (approximate) nash equilibria in zero-sum matrix games

Reference 25

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Observation 624861d4-73bb-4290-bf94-5ad0c15a5735 · outbound

This paper cites Mirror prox algorithm for multi-term composite minimization and semi-separable problems.

Solving Zero-Sum Games with Fewer Matrix-Vector Products Mirror prox algorithm for multi-term composite minimization and semi-separable problems

Reference 26

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Observation 3a25ede7-eb2e-4eb2-94c8-66ceba0dbd48 · outbound

This paper cites Closing the computational-query depth gap in parallel stochastic convex optimization.

Solving Zero-Sum Games with Fewer Matrix-Vector Products Closing the computational-query depth gap in parallel stochastic convex optimization

Reference 27

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Observation 6cdca6a5-cad5-43e7-a776-0c2f64006cd6 · outbound

This paper cites Reusing Samples in Variance Reduction.

Solving Zero-Sum Games with Fewer Matrix-Vector Products Reusing Samples in Variance Reduction

Reference 28

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Observation f441c358-3f9a-4327-ae1a-63987d21374a · outbound

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Solving Zero-Sum Games with Fewer Matrix-Vector Products Global linear convergence of Newton's method without strong-convexity or Lipschitz gradients

Reference 29

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Solving Zero-Sum Games with Fewer Matrix-Vector Products The oracle complexity of simplex-based matrix games: Linear separability and nash equilibria

Reference 30

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Solving Zero-Sum Games with Fewer Matrix-Vector Products Unresolved cited work

Reference 31

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Observation a4782438-104c-4e6a-b0b5-b53af2ce611c · outbound

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Solving Zero-Sum Games with Fewer Matrix-Vector Products The weighted majority algorithm

Reference 32

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Source-reported events for the cited work

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Observation 60b089f6-30ec-4297-a927-19dc892648d4 · outbound

This paper cites Accelerated Gradient Algorithms with Adaptive Subspace Search for Instance-Faster Optimization.

Solving Zero-Sum Games with Fewer Matrix-Vector Products Accelerated Gradient Algorithms with Adaptive Subspace Search for Instance-Faster Optimization

Reference 33

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Observation f523ef2f-60f3-4c0f-8b13-e11a8d24050d · outbound

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Solving Zero-Sum Games with Fewer Matrix-Vector Products Towards deep learning models resistant to adversarial attacks

Reference 34

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Source-reported events for the cited work

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Observation 5e8b9c8b-18eb-4829-a8c1-bef43a3af37b · outbound

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Solving Zero-Sum Games with Fewer Matrix-Vector Products A study of local approximations in information theory

Reference 35

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Source-reported events for the cited work

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Observation d4f301de-9c0b-4c1b-9cb4-cc8f8cb6c25d · outbound

This paper cites A logical calculus of the ideas immanent in nervous activity.

Solving Zero-Sum Games with Fewer Matrix-Vector Products A logical calculus of the ideas immanent in nervous activity

Reference 36

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T16:41:53.490839Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-15T16:41:53.091820Z digest=sha256:6e3bab8c835d70d40ca40f7068d0c8aa085fd1658e805784e8036bf76dcfca97

Observation b7a84680-8a0e-40d0-ab7d-bd3d40e3bc10 · outbound

This paper cites an unresolved cited work.

Solving Zero-Sum Games with Fewer Matrix-Vector Products Unresolved cited work

Reference 37

Resolution
unresolved
raw_fallback, observed 2026-08-15T16:41:53.476833Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-15T16:41:53.096123Z digest=sha256:1f019dba4880fe6686dcd286f591229eaa3e3dfa411bc4293c463be49f083feb

Observation 5c3dcf46-88e2-4719-b8cc-0ee2a4fb05a3 · outbound

This paper cites Randomized block krylov methods for stronger and faster approximate singular value decomposition.

Solving Zero-Sum Games with Fewer Matrix-Vector Products Randomized block krylov methods for stronger and faster approximate singular value decomposition

Reference 38

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T16:41:53.463282Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-15T16:41:53.100464Z digest=sha256:93576ca5b458f589292e2de0c872951cc85b9b49195a1a3f1336ef04e823ecd9

Observation cf77161f-2798-4628-b477-5f402ad93f54 · outbound

This paper cites Prox-method with rate of convergence o(1/t) for variational inequalities with lipschitz continuous monotone operators and smooth convex-concave saddle point problems.

Solving Zero-Sum Games with Fewer Matrix-Vector Products Prox-method with rate of convergence o(1/t) for variational inequalities with lipschitz continuous monotone operators and smooth convex-concave saddle point problems

Reference 39

Resolution
unresolved
no resolver link, observed 2026-08-15T16:41:53.104932Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T16:41:53.104932Z digest=sha256:978fcd21ee478865b9491d73dc617026f18024cc2bbe20848bd89977adfc22e2

Observation 2cf37bb4-7ed4-48a2-8593-80bf9d8c061f · outbound

This paper cites Problem complexity and method efficiency in optimization.

Solving Zero-Sum Games with Fewer Matrix-Vector Products Problem complexity and method efficiency in optimization

Reference 40

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T16:41:53.440891Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-15T16:41:53.109434Z digest=sha256:04fa7cd52ccf1f57aef6009da5a62b786aed035a0446b41b01e244d646279df1

Observation 932acd40-eafb-48fa-a5f1-f9bc850cd78f · outbound

This paper cites Smooth minimization of non-smooth functions.

Solving Zero-Sum Games with Fewer Matrix-Vector Products Smooth minimization of non-smooth functions

Reference 41

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T16:41:53.427469Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-15T16:41:53.114270Z digest=sha256:5a8cdd2989e2bdb98841852e9eb1e1620aeea1a1d7b7b684de316ae441ea0126

Observation 229ef9a0-bd45-49a1-9def-fa7a3e590124 · outbound

This paper cites Lower complexity bounds of first-order methods for convex-concave bilinear saddle-point problems.

Solving Zero-Sum Games with Fewer Matrix-Vector Products Lower complexity bounds of first-order methods for convex-concave bilinear saddle-point problems

Reference 42

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T16:41:53.412819Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-15T16:41:53.118502Z digest=sha256:8e741f9586f326f5711dda99eeebe484a92aa7dadeab20ebf0e8e0afde023254

Observation fea293be-59f8-479d-9645-96571c6366fb · outbound

This paper cites Stochastic variance reduction methods for saddle-point problems.

Solving Zero-Sum Games with Fewer Matrix-Vector Products Stochastic variance reduction methods for saddle-point problems

Reference 43

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T16:41:53.399163Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-15T16:41:53.122651Z digest=sha256:022cd8341c361762b8694cb5db1854ab4be403a104f7ef5f71443dd4f164d17b

Observation 36df7897-f0da-4dd0-bf8f-4c1afc867b1c · outbound

This paper cites Optimization, learning, and games with predictable sequences.

Solving Zero-Sum Games with Fewer Matrix-Vector Products Optimization, learning, and games with predictable sequences

Reference 44

Resolution
unresolved
no resolver link, observed 2026-08-15T16:41:53.127523Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T16:41:53.127523Z digest=sha256:e0ca20c1eaa10d3ae9878f1c34da9408e4525fe1c850586307643a8a53fb1641

Observation 218c16bf-dc8f-4267-969b-5e8e44bf122d · outbound

This paper cites Estimation of high-dimensional low-rank matrices.

Solving Zero-Sum Games with Fewer Matrix-Vector Products Estimation of high-dimensional low-rank matrices

Reference 45

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T16:41:53.376419Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-15T16:41:53.131197Z digest=sha256:f21a9d13d02502bd7b06feb09ca0670632244cf71fe26f8c6c02b5f396b5a2f7

Observation d934c9a9-35b7-4c86-88d1-7c2189410999 · outbound

This paper cites The perceptron: a probabilistic model for information storage and organization in the brain.

Solving Zero-Sum Games with Fewer Matrix-Vector Products The perceptron: a probabilistic model for information storage and organization in the brain

Reference 46

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T16:41:53.362309Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-15T16:41:53.134921Z digest=sha256:27b0bb1cef9aecb0a0bdee8593e92f78108c3c5b3972fff434e45f35ffcd0d79

Observation d1354fa1-59dd-4cdc-948e-b822f8ec5b7e · outbound

This paper cites Online learning and online convex optimization.

Solving Zero-Sum Games with Fewer Matrix-Vector Products Online learning and online convex optimization

Reference 47

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T16:41:53.346938Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-15T16:41:53.138672Z digest=sha256:7cac54a77d2fc05a00c1dc973fc6ec9ed42d5173f7fb95182d8c5cae1be78d15

Observation 0aa84e6d-cbd2-46d4-a6a2-668523adefe7 · outbound

This paper cites A smooth perceptron algorithm.

Solving Zero-Sum Games with Fewer Matrix-Vector Products A smooth perceptron algorithm

Reference 48

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T16:41:53.332715Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-15T16:41:53.142641Z digest=sha256:7c521ddcc0efcb2ef291a7d2674792f3430fefc92f2c12cbce2fb7f21ba445e1

Observation f13e8017-5529-47fd-b5cc-83f540933ec7 · outbound

This paper cites A Note on Preconditioning by Low-Stretch Spanning Trees.

Solving Zero-Sum Games with Fewer Matrix-Vector Products A Note on Preconditioning by Low-Stretch Spanning Trees

Reference 49

Resolution
unresolved
no resolver link, observed 2026-08-15T16:41:53.146581Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T16:41:53.146581Z digest=sha256:4ca03ca7f36838b36589d3ccbae70a647d63c7d11dc6bd848a1286d3baa6603e

Observation 0d8b8209-c1e6-4fc3-b3c7-8801f8fbf73c · outbound

This paper cites Tight complexity bounds for optimizing composite objectives.

Solving Zero-Sum Games with Fewer Matrix-Vector Products Tight complexity bounds for optimizing composite objectives

Reference 50

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T16:41:53.318975Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-15T16:41:53.150941Z digest=sha256:2a8a34eaa5f104cb38b761e56ba06ab1bedd10f09d6da15fde4f6a719874ae9a

Observation 40950fd6-c7c7-464d-8e7e-ea524aba9535 · outbound

This paper cites Saddle points and accelerated perceptron algorithms.

Solving Zero-Sum Games with Fewer Matrix-Vector Products Saddle points and accelerated perceptron algorithms

Reference 51

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T16:41:53.304398Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-15T16:41:53.154761Z digest=sha256:942e39874b4c2fb32ed231382bced00e82fd77a3e275901df6993adcae597c4a

Observation 69f6784b-c54d-48a4-b1bc-27a30501ab04 · outbound

This paper cites On lower iteration complexity bounds for the convex concave saddle point problems.

Solving Zero-Sum Games with Fewer Matrix-Vector Products On lower iteration complexity bounds for the convex concave saddle point problems

Reference 52

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T16:41:53.290935Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-15T16:41:53.158993Z digest=sha256:a30b7da198befa5fc8d3901139d3b2b63f2fd5d2475bda9e9bae30884306a2fe

Pith citing papers

No inbound Pith citation observations are available.