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Paper Citation Record · LEDGER

Learning-to-Optimize with PAC-Bayesian Guarantees: Theoretical Considerations and Practical Implementation

As of 13 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2404.03290.

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

pith.paper-citation-record.v1
2404.03290 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 2 of 2 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

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-12T14:07:24.620587Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-11T18:09:54.779434Z

Reference resolution

0 of 0 outbound references displayed

  • verified exact0
  • verified fuzzy0
  • unresolved0
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation b6f02e78-b017-484f-a288-50297d3af3e8 · inbound

Learning Algorithm Hyperparameters for Fast Parametric Convex Optimization cites this paper.

Learning Algorithm Hyperparameters for Fast Parametric Convex Optimization Learning-to-Optimize with PAC-Bayesian Guarantees: Theoretical Considerations and Practical Implementation

Reference 66

Resolution
unresolved
no resolver link, observed 2026-08-12T14:07:24.620587Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T14:07:24.620587Z digest=sha256:81128f57ae13b78c3688f92f427fa0faf083b8e461915fb227c972546a8781d3

Observation f041f4e5-720d-4901-8d89-f84e16c3168a · inbound

Deep Distributed Optimization for Large-Scale Quadratic Programming cites this paper.

Deep Distributed Optimization for Large-Scale Quadratic Programming Learning-to-Optimize with PAC-Bayesian Guarantees: Theoretical Considerations and Practical Implementation

Reference 53

Resolution
verified exact
local_arxiv, observed 2026-08-11T18:09:54.784110Z

Source-reported events for the cited work

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

source=arxiv_source observed=2026-08-11T18:09:54.672174Z digest=sha256:60c5de7a4d886f05924a4046a9f40b4030a45312147d3ab0c2dce93f520e6f70