Pith. sign in

Paper Citation Record · LEDGER

A Parameter-Free and Near-Optimal Zeroth-Order Algorithm for Stochastic Convex Optimization

As of 9 August 2026, this Paper Citation Record lists 61 of 61 outbound references and 1 inbound Pith citation observation for arXiv:2502.05600.

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

pith.paper-citation-record.v1
2502.05600 v2

Coverage vector

measured 61 of 61 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-08T18:49:52.651020Z

measured 62 of 62 standing notices

One-hop event checks from named stored sources.

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

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-06-27T04:33:10.554853Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-03T17:08:43.639380Z

Reference resolution

61 of 61 outbound references displayed

  • verified exact1
  • verified fuzzy39
  • unresolved21
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 36443e27-632d-4f5d-866d-93232843b052 · outbound

This paper cites Optimal algorithms for online convex optimization with multi-point bandit feedback.

A Parameter-Free and Near-Optimal Zeroth-Order Algorithm for Stochastic Convex Optimization Optimal algorithms for online convex optimization with multi-point bandit feedback

Reference 1

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T18:49:53.621933Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-08T18:49:52.232460Z digest=sha256:22d16c2c8d03685099b7dfc55d6a2ce6fafee2a5beb814e9b0f4d12f7fe540d8

Observation cc0ede2c-1047-4882-88bb-c90ae1dde36c · outbound

This paper cites Zeroth-order (non)-convex stochastic optimization via conditional gradient and gradient updates.

A Parameter-Free and Near-Optimal Zeroth-Order Algorithm for Stochastic Convex Optimization Zeroth-order (non)-convex stochastic optimization via conditional gradient and gradient updates

Reference 2

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T18:49:53.605312Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-08T18:49:52.238418Z digest=sha256:83c56f16fd0cf619a1114ee77ed61a0722b6a48c9d9203838c8335e9f5f632cf

Observation 6c808476-21ce-4e71-9a5a-2774c242cef5 · outbound

This paper cites Two-point step size gradient methods.

A Parameter-Free and Near-Optimal Zeroth-Order Algorithm for Stochastic Convex Optimization Two-point step size gradient methods

Reference 3

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T18:49:53.588145Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-08T18:49:52.245568Z digest=sha256:f4e384afd4051c369b53797d90ab96ca1d3ccab5ab723b0dfd85e3ff59128e50

Observation 5b53c678-f3ee-43fd-8b54-eb89d2d0a984 · outbound

This paper cites On the distance between two neural networks and the stability of learning.

A Parameter-Free and Near-Optimal Zeroth-Order Algorithm for Stochastic Convex Optimization On the distance between two neural networks and the stability of learning

Reference 4

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T18:49:53.573278Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-08T18:49:52.363895Z digest=sha256:8901990e3c109a6710e0f696895fd05c63bda47f4aeb035b51ba779f7dd2764f

Observation 79c50953-6838-49b8-8f51-fac545afb56e · outbound

This paper cites Training neural networks for and by interpolation.

A Parameter-Free and Near-Optimal Zeroth-Order Algorithm for Stochastic Convex Optimization Training neural networks for and by interpolation

Reference 5

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T18:49:53.557613Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-08T18:49:52.369289Z digest=sha256:cc3bfb80a7ff1e66cbba14c9b4cacc585e45260a1f77e6aaadedcd0ac4fec818

Observation 353b20ce-e4bc-47a6-a66d-bb89d0ac2495 · outbound

This paper cites Online learning with imperfect hints.

A Parameter-Free and Near-Optimal Zeroth-Order Algorithm for Stochastic Convex Optimization Online learning with imperfect hints

Reference 6

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T18:49:53.542119Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-08T18:49:52.374181Z digest=sha256:a23ff2f95a2fb5425a7cf6f49d807a82730c9fdaeb64821034a40f798a86bbd9

Observation a9eb4f30-1647-41a1-87c8-8755c05bc420 · outbound

This paper cites Making sgd parameter-free.

A Parameter-Free and Near-Optimal Zeroth-Order Algorithm for Stochastic Convex Optimization Making sgd parameter-free

Reference 7

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T18:49:53.525380Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-08T18:49:52.379630Z digest=sha256:f4a2c7a84b4c6f41d669d25ec627dd2530653a4cbe806bef7674b5ddc4ded1e2

Observation 0e041fac-feb5-4c12-94a1-e3bb2cfa14fe · outbound

This paper cites Libsvm: a library for support vector machines.

A Parameter-Free and Near-Optimal Zeroth-Order Algorithm for Stochastic Convex Optimization Libsvm: a library for support vector machines

Reference 8

Resolution
unresolved
no resolver link, observed 2026-08-08T18:49:52.384158Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T18:49:52.384158Z digest=sha256:fd42d66522f81dfe0dddbc9ff0f7a6964eed0d674c24b02dc1568c334dcca851

Observation daa39421-995d-44a2-8933-0447d4d2b89c · outbound

This paper cites Better parameter-free stochastic optimization with ode updates for coin-betting.

A Parameter-Free and Near-Optimal Zeroth-Order Algorithm for Stochastic Convex Optimization Better parameter-free stochastic optimization with ode updates for coin-betting

Reference 9

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T18:49:53.499234Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-08T18:49:52.388933Z digest=sha256:e90f972854d3bb09d7ed6eca977af8197b48b86703ab4b9bd707bc3d8420366e

Observation 926d5cdf-f65a-4d11-b96a-ece53bd8c0d1 · outbound

This paper cites Faster gradient-free algorithms for nonsmooth nonconvex stochastic optimization.

A Parameter-Free and Near-Optimal Zeroth-Order Algorithm for Stochastic Convex Optimization Faster gradient-free algorithms for nonsmooth nonconvex stochastic optimization

Reference 10

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T18:49:53.483655Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-08T18:49:52.393808Z digest=sha256:b647bf95223b9512d77b94f0062d432c1fd782b982952a0686e5fc8170811454

Observation 1ded3382-56d1-4850-ac7f-a68a0891a266 · outbound

This paper cites Black-box reductions for parameter-free online learning in banach spaces.

A Parameter-Free and Near-Optimal Zeroth-Order Algorithm for Stochastic Convex Optimization Black-box reductions for parameter-free online learning in banach spaces

Reference 11

Resolution
unresolved
no resolver link, observed 2026-08-08T18:49:52.398714Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T18:49:52.398714Z digest=sha256:164fa187b42a9ed407d54cb4e29c0d458112fd5a9eb778c61276b66c28360162

Observation b8185a1d-15a6-4d6a-ac81-f4ad1cefe6b8 · outbound

This paper cites Learning-rate-free learning by d-adaptation.

A Parameter-Free and Near-Optimal Zeroth-Order Algorithm for Stochastic Convex Optimization Learning-rate-free learning by d-adaptation

Reference 12

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T18:49:53.457840Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-08T18:49:52.403427Z digest=sha256:596567694c5e5da5bf4110d2266aa375889646c4a2a5fc182d007f15e1a8838f

Observation 712939a9-c8cb-4583-8880-78d86c8ea34e · outbound

This paper cites Adaptive subgradient methods for online learning and stochastic optimization.

A Parameter-Free and Near-Optimal Zeroth-Order Algorithm for Stochastic Convex Optimization Adaptive subgradient methods for online learning and stochastic optimization

Reference 13

Resolution
unresolved
no resolver link, observed 2026-08-08T18:49:52.408627Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T18:49:52.408627Z digest=sha256:8c5d81c82993e2d773e0330796a75dfe9f9886935e41556e4208026a21784578

Observation 1180fe6c-072e-4aca-a99d-33e348fbf2ac · outbound

This paper cites Duchi, Peter L.

A Parameter-Free and Near-Optimal Zeroth-Order Algorithm for Stochastic Convex Optimization Duchi, Peter L

Reference 14

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T18:49:53.431422Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-08T18:49:52.414034Z digest=sha256:e1699061160070a886f4eed132372f8f6b4b51fc31be877519ea15efffe61b85

Observation d3f7d536-5221-4fb0-91e6-96e7891e1491 · outbound

This paper cites Duchi, Michael I.

A Parameter-Free and Near-Optimal Zeroth-Order Algorithm for Stochastic Convex Optimization Duchi, Michael I

Reference 15

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T18:49:53.413062Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-08T18:49:52.418771Z digest=sha256:cc7bb42286968385124c40d5fc9b34882ab6bbd6f601bfc7d401bceeaa4fe91d

Observation 14d1b00e-205d-49dc-aeaa-ad097930f4f5 · outbound

This paper cites Probability: theory and examples , volume 49.

A Parameter-Free and Near-Optimal Zeroth-Order Algorithm for Stochastic Convex Optimization Probability: theory and examples , volume 49

Reference 16

Resolution
unresolved
no resolver link, observed 2026-08-08T18:49:52.423430Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T18:49:52.423430Z digest=sha256:36969ea7d4394660deecf287d556e38ce08c0cb7144350cec515b841000c555b

Observation 3921b38b-443a-4423-b38c-b22b036c45e0 · outbound

This paper cites Online convex optimization in the bandit setting: gradient descent without a gradient.

A Parameter-Free and Near-Optimal Zeroth-Order Algorithm for Stochastic Convex Optimization Online convex optimization in the bandit setting: gradient descent without a gradient

Reference 17

Resolution
unresolved
no resolver link, observed 2026-08-08T18:49:52.428331Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T18:49:52.428331Z digest=sha256:7153a57b4de9cddc075708e7b9ca6a200c6a37c201fc990fee0ab5db5725a8ea

Observation 4d75941c-75df-4b81-9158-cecc187c771f · outbound

This paper cites The Power of First-Order Smooth Optimization for Black-Box Non-Smooth Problems.

A Parameter-Free and Near-Optimal Zeroth-Order Algorithm for Stochastic Convex Optimization The Power of First-Order Smooth Optimization for Black-Box Non-Smooth Problems

Reference 18

Resolution
unresolved
no resolver link, observed 2026-08-08T18:49:52.434137Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T18:49:52.434137Z digest=sha256:fc63939a30041175420848ca7ae6d92298fa4b7ce5ea6d70046932d5ecf74ce3

Observation 58a3a714-5f17-4016-80aa-1e54b55c326f · outbound

This paper cites Stochastic first-and zeroth-order methods for nonconvex stochastic programming.

A Parameter-Free and Near-Optimal Zeroth-Order Algorithm for Stochastic Convex Optimization Stochastic first-and zeroth-order methods for nonconvex stochastic programming

Reference 19

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T18:49:53.384960Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-08T18:49:52.439291Z digest=sha256:d25d300e9584fbca9c7d20924dcb7ff81de9504dc1c3dded34905bce544cafb2

Observation 0db60a49-b7f7-4524-8a6d-9a69a7c71d73 · outbound

This paper cites Explaining and Harnessing Adversarial Examples.

A Parameter-Free and Near-Optimal Zeroth-Order Algorithm for Stochastic Convex Optimization Explaining and Harnessing Adversarial Examples

Reference 20

Resolution
unresolved
no resolver link, observed 2026-08-08T18:49:52.443797Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T18:49:52.443797Z digest=sha256:6b7aafd446e42653642186a5e044b6188594f25dd647c2169e12011ad4ea4f06

Observation 00a7f8f8-a63a-4958-87bf-b46924b3c75f · outbound

This paper cites Howard, Aaditya Ramdas, Jon McAuliffe, and Jasjeet Sekhon.

A Parameter-Free and Near-Optimal Zeroth-Order Algorithm for Stochastic Convex Optimization Howard, Aaditya Ramdas, Jon McAuliffe, and Jasjeet Sekhon

Reference 21

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T18:49:53.368206Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-08T18:49:52.449004Z digest=sha256:4d5600fda2d24b509b42205285c643c0de65b97a5c01376fdd10d909e3779010

Observation f80756ce-ce41-4c57-964b-dff24a5439f5 · outbound

This paper cites Prior Convictions: Black-Box Adversarial Attacks with Bandits and Priors.

A Parameter-Free and Near-Optimal Zeroth-Order Algorithm for Stochastic Convex Optimization Prior Convictions: Black-Box Adversarial Attacks with Bandits and Priors

Reference 22

Resolution
unresolved
no resolver link, observed 2026-08-08T18:49:52.454222Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T18:49:52.454222Z digest=sha256:b26d7c328deb5dacac0cfc3d8dfd6172dc9d4ce69f5a1a3bf059154519d08b52

Observation 3be57e68-84bb-4330-8a66-b174f43963c9 · outbound

This paper cites Dog is SGD’s best friend: A parameter-free dynamic step size schedule.

A Parameter-Free and Near-Optimal Zeroth-Order Algorithm for Stochastic Convex Optimization Dog is SGD’s best friend: A parameter-free dynamic step size schedule

Reference 23

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T18:49:53.353094Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-08T18:49:52.459571Z digest=sha256:3c7f928805e98d2ca07e3b39790fb7217ae4c5e1ab111d66d22b8f39a8b381cf

Observation 5d9ebbb4-67c5-436b-a6dd-002d3f298dd5 · outbound

This paper cites DoG is SGD's Best Friend: A Parameter-Free Dynamic Step Size Schedule.

A Parameter-Free and Near-Optimal Zeroth-Order Algorithm for Stochastic Convex Optimization DoG is SGD's Best Friend: A Parameter-Free Dynamic Step Size Schedule

Reference 24

Resolution
unresolved
no resolver link, observed 2026-08-08T18:49:52.465284Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T18:49:52.465284Z digest=sha256:1ba11bdd029ac5f936059e051a3c1fc613f49d9970682648a1597eb5e2fc5291

Observation cdf2a47a-bdc8-4904-99a8-1f27a62fb9e7 · outbound

This paper cites Parameter-free mirror descent.

A Parameter-Free and Near-Optimal Zeroth-Order Algorithm for Stochastic Convex Optimization Parameter-free mirror descent

Reference 25

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T18:49:53.337828Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-08T18:49:52.471227Z digest=sha256:5632a490df6148f0ab52b530936bf255e4442e6d68146f788b2abec1150baaa8

Observation 4a054e7d-17a7-4a92-a3c3-5d84cae457cc · outbound

This paper cites Tuning-Free Stochastic Optimization.

A Parameter-Free and Near-Optimal Zeroth-Order Algorithm for Stochastic Convex Optimization Tuning-Free Stochastic Optimization

Reference 26

Resolution
unresolved
no resolver link, observed 2026-08-08T18:49:52.476014Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T18:49:52.476014Z digest=sha256:13548cfbd7ac79454e986940fab3c9759fff1c0ccdd74ce1d4ebd1dbf7ef2052

Observation 34593c07-09ae-456a-b95a-eb90a06de1bf · outbound

This paper cites Stochastic estimation of the maximum of a regression function.

A Parameter-Free and Near-Optimal Zeroth-Order Algorithm for Stochastic Convex Optimization Stochastic estimation of the maximum of a regression function

Reference 27

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T18:49:53.322576Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-08T18:49:52.481334Z digest=sha256:c5231bb0d09804cd7e177d59bbb8e3ed059c25c8db65bdf4366a54cdb6673178

Observation 054a3d56-fb2e-4785-9644-e4821286377b · outbound

This paper cites Kingma and Jimmy Ba.

A Parameter-Free and Near-Optimal Zeroth-Order Algorithm for Stochastic Convex Optimization Kingma and Jimmy Ba

Reference 28

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T18:49:53.306487Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-08T18:49:52.485898Z digest=sha256:ef70ab281d9e21583a703d5289aadc9648252d0a275305b7ebeb4b0f9d44fc28

Observation 1970435e-a449-404e-9ad3-12ab1903a349 · outbound

This paper cites An algorithm with optimal dimension-dependence for zero-order nonsmooth nonconvex stochastic optimization.

A Parameter-Free and Near-Optimal Zeroth-Order Algorithm for Stochastic Convex Optimization An algorithm with optimal dimension-dependence for zero-order nonsmooth nonconvex stochastic optimization

Reference 29

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T18:49:53.290732Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-08T18:49:52.490255Z digest=sha256:deeb4673c9e9305484d46c1f036dd42b84b3ad3476337ea13b2da9c5e6e47d8a

Observation 33eba5b0-4c0f-4fc2-b613-294a55961dd0 · outbound

This paper cites Optimal and parameter-free gradient minimization methods for convex and nonconvex optimization.

A Parameter-Free and Near-Optimal Zeroth-Order Algorithm for Stochastic Convex Optimization Optimal and parameter-free gradient minimization methods for convex and nonconvex optimization

Reference 30

Resolution
unresolved
no resolver link, observed 2026-08-08T18:49:52.494744Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T18:49:52.494744Z digest=sha256:eff30659135affb31000e1b8350d4ef07c730dd624bb59e646330313cd9685cd

Observation dc27d49f-6d70-4de7-8556-123ac7ef1ae7 · outbound

This paper cites A simple uniformly optimal method without line search for convex optimization.

A Parameter-Free and Near-Optimal Zeroth-Order Algorithm for Stochastic Convex Optimization A simple uniformly optimal method without line search for convex optimization

Reference 31

Resolution
unresolved
no resolver link, observed 2026-08-08T18:49:52.499732Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T18:49:52.499732Z digest=sha256:413407e458b911738d4d5a1e3859503a512878072b6cf5f30192ddb21f8f0c08

Observation f217a5b6-8e84-4a05-b1aa-b42156f5002b · outbound

This paper cites Gradient-free methods for deterministic and stochastic nonsmooth nonconvex optimization.

A Parameter-Free and Near-Optimal Zeroth-Order Algorithm for Stochastic Convex Optimization Gradient-free methods for deterministic and stochastic nonsmooth nonconvex optimization

Reference 32

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T18:49:53.275887Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-08T18:49:52.504847Z digest=sha256:7ff2bbe31bd5aa848e007242cbc8e1a5921916d3836e3f36d3acae4546df0c86

Observation 05f453e7-34da-4fc0-9886-15ded1f5be23 · outbound

This paper cites A primer on zeroth-order optimization in signal processing and machine learning: Principals, recent advances, and applications.

A Parameter-Free and Near-Optimal Zeroth-Order Algorithm for Stochastic Convex Optimization A primer on zeroth-order optimization in signal processing and machine learning: Principals, recent advances, and applications

Reference 33

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T18:49:53.260538Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-08T18:49:52.510156Z digest=sha256:4bacd1dd4e4762d211c9c7754773543b3b54900881f52307eaa21913b3ee79bf

Observation 0930d8ef-be91-4866-8abe-8e2b6c85ac9c · outbound

This paper cites Delving into Transferable Adversarial Examples and Black-box Attacks.

A Parameter-Free and Near-Optimal Zeroth-Order Algorithm for Stochastic Convex Optimization Delving into Transferable Adversarial Examples and Black-box Attacks

Reference 34

Resolution
unresolved
no resolver link, observed 2026-08-08T18:49:52.515847Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T18:49:52.515847Z digest=sha256:4b2d5a39764369f1434c2b796599598f8997ffd59339d004592599b3ec02c50e

Observation bf3722ba-ab99-47d5-89d0-3cdb437fb0d4 · outbound

This paper cites Stochastic polyak step-size for sgd: An adaptive learning rate for fast convergence.

A Parameter-Free and Near-Optimal Zeroth-Order Algorithm for Stochastic Convex Optimization Stochastic polyak step-size for sgd: An adaptive learning rate for fast convergence

Reference 35

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T18:49:53.243696Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-08T18:49:52.521812Z digest=sha256:6c6b4294df66e9e693762ae618dc5d53c06dbc1e91a42beb8d9734aa84b19e43

Observation d51b7833-834a-4ed9-8703-ac7a0748b03e · outbound

This paper cites Achieving all with no parameters: Adanormalhedge.

A Parameter-Free and Near-Optimal Zeroth-Order Algorithm for Stochastic Convex Optimization Achieving all with no parameters: Adanormalhedge

Reference 36

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T18:49:53.228746Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-08T18:49:52.526866Z digest=sha256:0dedcde5ce4352ca1d18e8669a5cdfef631ce087bd7907638db481e1911b7e13

Observation f12b0d7b-c90f-4163-b0c1-79578da3fa5c · outbound

This paper cites Simple random search provides a competitive approach to reinforcement learning.

A Parameter-Free and Near-Optimal Zeroth-Order Algorithm for Stochastic Convex Optimization Simple random search provides a competitive approach to reinforcement learning

Reference 37

Resolution
unresolved
no resolver link, observed 2026-08-08T18:49:52.531774Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T18:49:52.531774Z digest=sha256:3af7ea86d9af8eccc90dbe178d30970392bf761018d566be961e91c079c9a36b

Observation 734e02e0-00d2-4898-9b3d-b0b137e62ddc · outbound

This paper cites Lipschitz and comparator-norm adaptivity in online learning.

A Parameter-Free and Near-Optimal Zeroth-Order Algorithm for Stochastic Convex Optimization Lipschitz and comparator-norm adaptivity in online learning

Reference 38

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T18:49:53.213279Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-08T18:49:52.536874Z digest=sha256:3a05fad11164355aa8e66a91c7274ee780a5194b7788d282f656cd18baa4d2bf

Observation 8473a882-f7ce-49a1-974d-f399a1fa4c53 · outbound

This paper cites Adaptive First-and Zeroth-order Methods for Weakly Convex Stochastic Optimization Problems.

A Parameter-Free and Near-Optimal Zeroth-Order Algorithm for Stochastic Convex Optimization Adaptive First-and Zeroth-order Methods for Weakly Convex Stochastic Optimization Problems

Reference 39

Resolution
unresolved
no resolver link, observed 2026-08-08T18:49:52.541953Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T18:49:52.541953Z digest=sha256:4678c13c4befee41e2835e57867fb1b6e1a545ac444d0eb840b765940b8276be

Observation fcc7e03f-e52c-4c43-85bf-010e8a6fe782 · outbound

This paper cites Random gradient-free minimization of convex functions.

A Parameter-Free and Near-Optimal Zeroth-Order Algorithm for Stochastic Convex Optimization Random gradient-free minimization of convex functions

Reference 40

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T18:49:53.197775Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-08T18:49:52.547016Z digest=sha256:2bda37cb64456e540f1e3f882381a989ca81f4252fa19e7f735874aaef6b34d9

Observation 285d6089-0263-454f-9cd3-f15216d509d1 · outbound

This paper cites Coin betting and parameter-free online learning.Advances in Neural Information Processing Systems, 29, 2016.

A Parameter-Free and Near-Optimal Zeroth-Order Algorithm for Stochastic Convex Optimization Coin betting and parameter-free online learning.Advances in Neural Information Processing Systems, 29, 2016

Reference 41

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T18:49:53.181777Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-08T18:49:52.551831Z digest=sha256:4bbc578662bad26108d54872eb5e8750f9758a96cda539651a521f324458a8e7

Observation 24d1bba4-f3bb-453d-aa36-1a2fe03f891c · outbound

This paper cites Training deep networks without learning rates through coin betting.

A Parameter-Free and Near-Optimal Zeroth-Order Algorithm for Stochastic Convex Optimization Training deep networks without learning rates through coin betting

Reference 42

Resolution
unresolved
no resolver link, observed 2026-08-08T18:49:52.556495Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T18:49:52.556495Z digest=sha256:0a41b42939c7145ed32273650e7a87f1a834cc545948b2f5d46e10c076b39b59

Observation b7f04ed1-5b0f-4876-a75e-bb4660376cb2 · outbound

This paper cites A stochastic line search method with expected complexity analysis.

A Parameter-Free and Near-Optimal Zeroth-Order Algorithm for Stochastic Convex Optimization A stochastic line search method with expected complexity analysis

Reference 43

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T18:49:53.156096Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-08T18:49:52.561676Z digest=sha256:d46ec8b985d48bc762db2e6e0663f74ffd4c0b16ecc85957c7d2b546be52ec4d

Observation fc62997b-e804-40c3-b3d6-e2734fb9a2c6 · outbound

This paper cites Introduction to optimization.

A Parameter-Free and Near-Optimal Zeroth-Order Algorithm for Stochastic Convex Optimization Introduction to optimization

Reference 44

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T18:49:53.141341Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-08T18:49:52.566525Z digest=sha256:4c7ad3310ba8461cfd3e10a6cf17ddad160f261fde05c08b836f0637bd4a0fe6

Observation d8ce338d-5279-476f-a4c1-d9b3b770bebc · outbound

This paper cites An optimal structured zeroth-order algorithm for non-smooth optimization.

A Parameter-Free and Near-Optimal Zeroth-Order Algorithm for Stochastic Convex Optimization An optimal structured zeroth-order algorithm for non-smooth optimization

Reference 45

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T18:49:53.126200Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-08T18:49:52.571180Z digest=sha256:7f3881a62a2850c53f6c21b34c526337eed13a08a64e37dbc72e6d4c2ef5de56

Observation dd2617a2-bfb0-4695-9587-7920a1fd7f2d · outbound

This paper cites L4: Practical loss-based stepsize adaptation for deep learning.

A Parameter-Free and Near-Optimal Zeroth-Order Algorithm for Stochastic Convex Optimization L4: Practical loss-based stepsize adaptation for deep learning

Reference 46

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T18:49:53.110659Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-08T18:49:52.575770Z digest=sha256:318173aa0fc7a1f9fdeb72b77a402d9860ef491ef97861bad210ecf3b2184f30

Observation 8e3803c8-7a80-4b85-9116-d73adb6d00de · outbound

This paper cites Understanding adversarial training: Increasing local stability of supervised models through robust optimization.

A Parameter-Free and Near-Optimal Zeroth-Order Algorithm for Stochastic Convex Optimization Understanding adversarial training: Increasing local stability of supervised models through robust optimization

Reference 47

Resolution
unresolved
no resolver link, observed 2026-08-08T18:49:52.580588Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T18:49:52.580588Z digest=sha256:1ae203a303bedbd08dc340e2a1e191ceb831df20cfd6e97477ab4a8625174141

Observation 085cb9c7-2cc6-43ea-99a8-e864bcd122a8 · outbound

This paper cites Online learning and online convex optimization.

A Parameter-Free and Near-Optimal Zeroth-Order Algorithm for Stochastic Convex Optimization Online learning and online convex optimization

Reference 48

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T18:49:53.085569Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-08T18:49:52.585516Z digest=sha256:ddd5caa6395c3cfd094f35a63fed53069a5c68e7b40086626ed4c8e577747f8b

Observation 98fffc83-472d-4b6d-aaf2-ff2a1ebfa910 · outbound

This paper cites An optimal algorithm for bandit and zero-order convex optimization with two-point feedback.

A Parameter-Free and Near-Optimal Zeroth-Order Algorithm for Stochastic Convex Optimization An optimal algorithm for bandit and zero-order convex optimization with two-point feedback

Reference 49

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T18:49:53.070911Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-08T18:49:52.590368Z digest=sha256:b04c77dd86d22b625f4ca52017c53da35dc904086080bc75b73c68b5b022ebf1

Observation f0f59710-0205-4263-a51c-5cae4f5a2b3b · outbound

This paper cites Adafactor: Adaptive learning rates with sublinear memory cost.

A Parameter-Free and Near-Optimal Zeroth-Order Algorithm for Stochastic Convex Optimization Adafactor: Adaptive learning rates with sublinear memory cost

Reference 50

Resolution
unresolved
no resolver link, observed 2026-08-08T18:49:52.595476Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T18:49:52.595476Z digest=sha256:9965e994fdca9b9c95cf57bdfff616d3557d4c756cc5732a0059aecd09c09405

Observation bc115a12-d3ad-4bd6-abf6-5fe4216d24b9 · outbound

This paper cites No-Regret Algorithms for Unconstrained Online Convex Optimization.

A Parameter-Free and Near-Optimal Zeroth-Order Algorithm for Stochastic Convex Optimization No-Regret Algorithms for Unconstrained Online Convex Optimization

Reference 51

Resolution
verified exact
local_arxiv, observed 2026-08-08T18:49:52.750138Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-08T18:49:52.600678Z digest=sha256:453d4c6453e0563218a7903c435163115e787938fdc451fa32a28f71e9b8aafd

Observation d71d5497-ba80-4ca8-9645-f52c1a5bf6d6 · outbound

This paper cites Barzilai-borwein step size for stochastic gradient descent.

A Parameter-Free and Near-Optimal Zeroth-Order Algorithm for Stochastic Convex Optimization Barzilai-borwein step size for stochastic gradient descent

Reference 52

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T18:49:53.045720Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-08T18:49:52.606902Z digest=sha256:86656eb09bd100009a40965ef5688e33384cdf9319d1bfdd452b5fb2c166d276

Observation dc951868-083c-4e03-a5ec-5ccb48f8b99e · outbound

This paper cites Lecture 6.5-rmsprop: Divide the gradient by a running average of its recent magnitude.

A Parameter-Free and Near-Optimal Zeroth-Order Algorithm for Stochastic Convex Optimization Lecture 6.5-rmsprop: Divide the gradient by a running average of its recent magnitude

Reference 53

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T18:49:53.029878Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-08T18:49:52.611779Z digest=sha256:d00d1175240cbc8db5d9e66147134403f30afc8f0660b038a33ac31ea9c0363f

Observation 10e11de0-ed7b-44a9-bfee-d88d140b2a23 · outbound

This paper cites Painless stochastic gradient: Interpolation, line-search, and convergence rates.

A Parameter-Free and Near-Optimal Zeroth-Order Algorithm for Stochastic Convex Optimization Painless stochastic gradient: Interpolation, line-search, and convergence rates

Reference 54

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T18:49:53.011371Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-08T18:49:52.616880Z digest=sha256:4e278238d989eb9c70b623c089650a69d7ba6d3630b898d166994796210d4fdd

Observation aa1402f7-232c-4421-b504-95cf30a54ef5 · outbound

This paper cites Provable adaptivity of adam under non-uniform smoothness.

A Parameter-Free and Near-Optimal Zeroth-Order Algorithm for Stochastic Convex Optimization Provable adaptivity of adam under non-uniform smoothness

Reference 55

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T18:49:52.995430Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-08T18:49:52.621734Z digest=sha256:bbace6772efcf04575f75ad78ad35d6c5bd2e51ebe60c79cc7edb13ed7c2606f

Observation 5c529546-8b92-4d29-9093-202f7d805c30 · outbound

This paper cites Generalized polyak step size for first order optimization with momentum.

A Parameter-Free and Near-Optimal Zeroth-Order Algorithm for Stochastic Convex Optimization Generalized polyak step size for first order optimization with momentum

Reference 56

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T18:49:52.979118Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-08T18:49:52.626297Z digest=sha256:7bfce6c3635b489756ee06a68ff305ddb556dbd235e616784dc958c948a98a46

Observation c9ff0660-ef8c-4070-92d9-744581c06cf7 · outbound

This paper cites Finite sample convergence rates of zero-order stochastic optimization methods.

A Parameter-Free and Near-Optimal Zeroth-Order Algorithm for Stochastic Convex Optimization Finite sample convergence rates of zero-order stochastic optimization methods

Reference 57

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T18:49:52.961741Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-08T18:49:52.631453Z digest=sha256:508ca120b9be1cd02fc95bf0b0e7aef6e09177ab928cbb21cd1a264325e0ae03

Observation 7c4f2928-33fc-4b73-ac9a-9a4e2a62b55c · outbound

This paper cites Large Batch Training of Convolutional Networks.

A Parameter-Free and Near-Optimal Zeroth-Order Algorithm for Stochastic Convex Optimization Large Batch Training of Convolutional Networks

Reference 58

Resolution
unresolved
no resolver link, observed 2026-08-08T18:49:52.635960Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T18:49:52.635960Z digest=sha256:c89e6089a316225e6eceaa52e6e8a3bf65223bce6d7e34f97f82d44fc6b5f797

Observation 7ca883b3-5051-4eaa-8feb-4f2d4c62b912 · outbound

This paper cites On stochastic gradient and subgradient methods with adaptive steplength sequences.

A Parameter-Free and Near-Optimal Zeroth-Order Algorithm for Stochastic Convex Optimization On stochastic gradient and subgradient methods with adaptive steplength sequences

Reference 59

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T18:49:52.945988Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-08T18:49:52.640806Z digest=sha256:86e8fda80734fc35fbd693acbef12e181d4c3c178602993496d844f17b2546c4

Observation 8fe9f462-59d6-449d-a397-e640aa3981fc · outbound

This paper cites ADADELTA: An Adaptive Learning Rate Method.

A Parameter-Free and Near-Optimal Zeroth-Order Algorithm for Stochastic Convex Optimization ADADELTA: An Adaptive Learning Rate Method

Reference 60

Resolution
unresolved
no resolver link, observed 2026-08-08T18:49:52.645495Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T18:49:52.645495Z digest=sha256:245b7a3e16ccfe1c3f1aae527c5340a2473dd7f429a125b00d08c755518404cb

Observation ed6a2b6b-07e1-4ec9-bb3d-90f393f4698a · outbound

This paper cites Adam-mini: Use Fewer Learning Rates To Gain More.

A Parameter-Free and Near-Optimal Zeroth-Order Algorithm for Stochastic Convex Optimization Adam-mini: Use Fewer Learning Rates To Gain More

Reference 61

Resolution
unresolved
no resolver link, observed 2026-08-08T18:49:52.651020Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T18:49:52.651020Z digest=sha256:308b112a3bd3fec210370b13dc6f922f544e832248f7b406067e9e06a0975fbe

Pith citing papers

Observation ae9b23cc-19b6-483d-bdb7-406c239036d5 · inbound

Zero-order Parameter-free Optimization for LMO-based Methods: Novel Approach for Efficient Fine-tuning cites this paper.

Zero-order Parameter-free Optimization for LMO-based Methods: Novel Approach for Efficient Fine-tuning A Parameter-Free and Near-Optimal Zeroth-Order Algorithm for Stochastic Convex Optimization

Reference 72

Resolution
verified exact
arxiv_id, observed 2026-07-03T17:08:43.640812Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-06-27T04:33:10.554853Z digest=sha256:91dbd30938916d27d1138a94c18dea73649d3c827f6889ff410b3311bf487e51