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Paper Citation Record · LEDGER

Wasserstein Distributionally Robust Optimization: Theory and Applications in Machine Learning

As of 12 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:1908.08729.

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

pith.paper-citation-record.v1
1908.08729 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 2026-08-12T06:34:41.77262+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-10T00:49:29.970982Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-10T00:49:30.328472Z

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 b7b36927-4cfe-4216-a1ae-60bb3e5d9bed · inbound

Robust Mean Estimation With Auxiliary Samples cites this paper.

Robust Mean Estimation With Auxiliary Samples Wasserstein Distributionally Robust Optimization: Theory and Applications in Machine Learning

Reference 7

Resolution
verified exact
local_arxiv, observed 2026-08-10T00:49:30.335872Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-10T00:49:29.970982Z digest=sha256:7fba86cf3bef97233630162b109f24458564ad7fa6a008c9e2f1039fc3dca974

Observation bdc05918-76c4-40a6-b64c-b3f79a3a3899 · inbound

Learning Predictive Ambiguity Sets for Decision-Focused Distributionally Robust Optimization cites this paper.

Learning Predictive Ambiguity Sets for Decision-Focused Distributionally Robust Optimization Wasserstein Distributionally Robust Optimization: Theory and Applications in Machine Learning

Reference 15

Resolution
unresolved
no resolver link, observed 2026-07-14T15:19:17.267890Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-07-14T15:19:17.267890Z digest=sha256:9b658e63746a04926af6b7ce63c91ef294f4f174d95f61ca7f4d3551ee3cc5a9