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Paper Citation Record · LEDGER

Ruppert-Polyak averaging for Stochastic Order Oracle

As of 13 August 2026, this Paper Citation Record lists 20 of 20 outbound references and 0 inbound Pith citation observations for arXiv:2411.15866.

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

pith.paper-citation-record.v1
2411.15866 v1

Coverage vector

measured 20 of 20 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-12T13:55:43.128930Z

measured 20 of 20 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-13T06:32:02.005865+00:00

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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

20 of 20 outbound references displayed

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  • verified fuzzy6
  • unresolved14
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External citation measurements

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Outbound references

Observation bcf5b9e2-28c4-4e05-91d8-19dce015a2a9 · outbound

This paper cites Zoo: Zeroth order optimization based black-box attacks to deep neural networks without training substitute models.

Ruppert-Polyak averaging for Stochastic Order Oracle Zoo: Zeroth order optimization based black-box attacks to deep neural networks without training substitute models

Reference 1

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Observation fd93b66c-a12c-45b6-b63c-3413d58a8ff0 · outbound

This paper cites Practical black-box attacks against machine learning.

Ruppert-Polyak averaging for Stochastic Order Oracle Practical black-box attacks against machine learning

Reference 2

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Observation 5e5e2f6a-3fdc-4489-8a0a-8c683ce6d9fb · outbound

This paper cites Introduction to derivative-free optimization.

Ruppert-Polyak averaging for Stochastic Order Oracle Introduction to derivative-free optimization

Reference 3

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source=pdf_text observed=2026-08-12T13:55:43.043725Z digest=sha256:ba0f9e34bf4a7eb86a2a375845668519a38af2cf6839a2821644a7d24e1af5db

Observation 91c2a779-620c-4ce3-b3eb-cf0f008796ba · outbound

This paper cites Derivative-free optimization methods.

Ruppert-Polyak averaging for Stochastic Order Oracle Derivative-free optimization methods

Reference 4

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source=pdf_text observed=2026-08-12T13:55:43.048661Z digest=sha256:8485b06b888be450fc06ec4e8de5bbca86b69c749bef767ed55846225eb745f3

Observation c11513d6-9d16-407a-b038-04becfbf1ecd · outbound

This paper cites Zeroth-Order Optimization Meets Human Feedback: Provable Learning via Ranking Oracles.

Ruppert-Polyak averaging for Stochastic Order Oracle Zeroth-Order Optimization Meets Human Feedback: Provable Learning via Ranking Oracles

Reference 5

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source=pdf_text observed=2026-08-12T13:55:43.053879Z digest=sha256:0d3aa44676a85cf77f218fc80628adf33d81aa377a9da4323dbdf8d46136eda7

Observation 59181db6-7b6f-4fd9-9547-ded3aec42e5c · outbound

This paper cites Training language models to follow instructions with human feedback.

Ruppert-Polyak averaging for Stochastic Order Oracle Training language models to follow instructions with human feedback

Reference 6

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Observation c50b7f31-9622-4480-b011-fd33d84ad9ee · outbound

This paper cites Acceleration Exists! Optimization Problems When Oracle Can Only Compare Objective Function Values.

Ruppert-Polyak averaging for Stochastic Order Oracle Acceleration Exists! Optimization Problems When Oracle Can Only Compare Objective Function Values

Reference 7

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Observation 669bbad4-f18a-4f5d-ba93-e01e29eb7c6f · outbound

This paper cites Acceleration of stochastic approximation by averaging.

Ruppert-Polyak averaging for Stochastic Order Oracle Acceleration of stochastic approximation by averaging

Reference 8

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source=pdf_text observed=2026-08-12T13:55:43.070818Z digest=sha256:5883d2f0de054e12032501ff2f90019f598ec1b850925092a36db47fd8fb7df5

Observation 4174143f-2b63-4ec8-9168-073374cfba7a · outbound

This paper cites Dueling convex optimization.

Ruppert-Polyak averaging for Stochastic Order Oracle Dueling convex optimization

Reference 9

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Observation 2b430710-ccc3-4e1b-a9be-4411db55dd8f · outbound

This paper cites Optimal pseudogradient adaptation algorithms.

Ruppert-Polyak averaging for Stochastic Order Oracle Optimal pseudogradient adaptation algorithms

Reference 10

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No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-12T13:55:43.080313Z digest=sha256:8500218262fff0773a4c991b2102fcb0ba12ef528b550b3eba6cf9cd87066582

Observation 7594892a-c9cf-49a8-aa01-7817e045dfe9 · outbound

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

Ruppert-Polyak averaging for Stochastic Order Oracle Random gradient-free minimization of convex functions

Reference 11

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Observation 2980f09e-6568-4a42-bcb2-14d81d417f6e · outbound

This paper cites Convex optimization.

Ruppert-Polyak averaging for Stochastic Order Oracle Convex optimization

Reference 12

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Observation b62ac359-09f9-4f57-adfd-44ab1e0ea597 · outbound

This paper cites Lectures on convex optimization, volume 137.

Ruppert-Polyak averaging for Stochastic Order Oracle Lectures on convex optimization, volume 137

Reference 13

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source=pdf_text observed=2026-08-12T13:55:43.095678Z digest=sha256:46cdba99f5010afda74efba2a862e7ee76a15a22bd25ac00748b4955a5dd7824

Observation 9a02561d-fc80-492d-b8a3-25a1381143d8 · outbound

This paper cites Revisiting normalized gradient descent: Fast evasion of saddle points.

Ruppert-Polyak averaging for Stochastic Order Oracle Revisiting normalized gradient descent: Fast evasion of saddle points

Reference 14

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Observation 87ad777b-034e-443f-a435-ca7dafba4b04 · outbound

This paper cites Optimal non-asymptotic analysis of the ruppert–polyak averaging stochastic algorithm.

Ruppert-Polyak averaging for Stochastic Order Oracle Optimal non-asymptotic analysis of the ruppert–polyak averaging stochastic algorithm

Reference 15

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Observation 515ab521-9122-4feb-bf5b-600e9fc8ec39 · outbound

This paper cites an unresolved cited work.

Ruppert-Polyak averaging for Stochastic Order Oracle Unresolved cited work

Reference 16

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Observation 7d2fdcb7-1427-46a9-b736-bbf33f4ae351 · outbound

This paper cites (a) φ(x + z) = c√ d x+z ∥x+z∥ is a Lebesgue-integrable function of z for each x ∈ X.

Ruppert-Polyak averaging for Stochastic Order Oracle (a) φ(x + z) = c√ d x+z ∥x+z∥ is a Lebesgue-integrable function of z for each x ∈ X

Reference 17

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No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

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Observation 0aa2df37-0c45-4206-909a-86db56cb3b6c · outbound

This paper cites an unresolved cited work.

Ruppert-Polyak averaging for Stochastic Order Oracle Unresolved cited work

Reference 18

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Observation f1ec49e1-7b55-49a7-aed5-aba3bfcf868d · outbound

This paper cites an unresolved cited work.

Ruppert-Polyak averaging for Stochastic Order Oracle Unresolved cited work

Reference 19

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Observation e91ddcbd-e2be-4ffd-9bc0-32a1388865ec · outbound

This paper cites (a) ∇xφ(x + z) = c√ d [ 1 ∥x+z∥ I − (x+z)(x+z)T ∥x+z∥3 ] is a Lebesgue-integrable function of z for each x ∈ X (proved in 2a).

Ruppert-Polyak averaging for Stochastic Order Oracle (a) ∇xφ(x + z) = c√ d [ 1 ∥x+z∥ I − (x+z)(x+z)T ∥x+z∥3 ] is a Lebesgue-integrable function of z for each x ∈ X (proved in 2a)

Reference 20

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No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

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Pith citing papers

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