Paper Citation Record · LEDGER

DRO: A Python Library for Distributionally Robust Optimization in Machine Learning

As of 15 August 2026, this Paper Citation Record lists 14 of 14 outbound references and 2 inbound Pith citation observations for arXiv:2505.23565.

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

pith.paper-citation-record.v1
2505.23565 v1

Coverage vector

measured 14 of 14 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T12:45:46.487410Z

measured 16 of 16 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-15T06:32:42.880941+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T11:58:38.461206Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-07T10:40:37.625053Z

Reference resolution

14 of 14 outbound references displayed

verified exact2
verified fuzzy5
unresolved7
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 818d52b6-4354-4e6d-a220-f17520424272 · outbound

This paper cites (2) (Generalized) f -divergence.

DRO: A Python Library for Distributionally Robust Optimization in Machine Learning (2) (Generalized) f -divergence

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:45:47.643367Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 653529e1-78a0-4d25-ad66-9ae0fba7abed · outbound

This paper cites Unifying distributionally robust optimization via optimal transport theory.

DRO: A Python Library for Distributionally Robust Optimization in Machine Learning Unifying distributionally robust optimization via optimal transport theory

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-07T12:45:45.422655Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3e895c9d-5c59-4267-814a-b94f018567e7 · outbound

This paper cites Distributionally Robust Optimization and Robust Statistics.

DRO: A Python Library for Distributionally Robust Optimization in Machine Learning Distributionally Robust Optimization and Robust Statistics

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-07T12:45:45.544664Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 06e5ce70-db75-416f-9802-dc13fcad6ee5 · outbound

This paper cites Rethinking Distribution Shifts: Empirical Analysis and Modeling for Tabular Data.

DRO: A Python Library for Distributionally Robust Optimization in Machine Learning Rethinking Distribution Shifts: Empirical Analysis and Modeling for Tabular Data

Reference 7

Resolution: verified exact; local_arxiv, observed 2026-08-07T12:45:46.871235Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 344f7750-256d-40ad-90a2-6d83875bad7b · outbound

This paper cites skwdro: a library for wasserstein distributionally robust machine learning.

DRO: A Python Library for Distributionally Robust Optimization in Machine Learning skwdro: a library for wasserstein distributionally robust machine learning

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-07T12:45:46.078250Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 123d65de-35b9-4afe-9370-7b0a781ff175 · outbound

This paper cites F unction Source Description classificationbasic Custom Multi-class Gaussian blobs on a sphere; baseline data generator.

DRO: A Python Library for Distributionally Robust Optimization in Machine Learning F unction Source Description classificationbasic Custom Multi-class Gaussian blobs on a sphere; baseline data generator

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:45:48.091581Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation a757f7f9-303e-4d57-bc43-cfdf1424f2fb · outbound

This paper cites lad”, “svm.

DRO: A Python Library for Distributionally Robust Optimization in Machine Learning lad”, “svm

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:45:47.886078Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 9b2ce38d-4dd0-4b9d-a4fd-341dcbd22aa9 · outbound

This paper cites Learning from a Biased Sample.

DRO: A Python Library for Distributionally Robust Optimization in Machine Learning Learning from a Biased Sample

Reference 2000

Resolution: unresolved; no resolver link, observed 2026-08-07T12:45:45.979223Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f8289f45-bee2-48f2-9b4d-5a45302892e0 · outbound

This paper cites Optimizer's Information Criterion: Dissecting and Correcting Bias in Data-Driven Optimization.

DRO: A Python Library for Distributionally Robust Optimization in Machine Learning Optimizer's Information Criterion: Dissecting and Correcting Bias in Data-Driven Optimization

Reference 2013

Resolution: unresolved; no resolver link, observed 2026-08-07T12:45:45.683237Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation cdd7daf4-85fc-4f26-95b8-81c4b8d83502 · outbound

This paper cites Distributionally Robust Optimization.

DRO: A Python Library for Distributionally Robust Optimization in Machine Learning Distributionally Robust Optimization

Reference 2018

Resolution: unresolved; no resolver link, observed 2026-08-07T12:45:45.806213Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b062757c-9883-4511-b9f0-5f85ab21e240 · outbound

This paper cites Data-driven optimal transport cost selection for distributionally robust optimization.

DRO: A Python Library for Distributionally Robust Optimization in Machine Learning Data-driven optimal transport cost selection for distributionally robust optimization

Reference 2022

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:45:48.336550Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation b9d9818b-ff68-4fe9-a9f9-3c0e279e819c · outbound

This paper cites Holistic Robust Data-Driven Decisions.

DRO: A Python Library for Distributionally Robust Optimization in Machine Learning Holistic Robust Data-Driven Decisions

Reference 2023

Resolution: verified exact; local_arxiv, observed 2026-08-07T12:45:47.191105Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation fbc442de-760a-41d2-806a-f5ca21127e75 · outbound

This paper cites Sinkhorn Distributionally Robust Optimization.

DRO: A Python Library for Distributionally Robust Optimization in Machine Learning Sinkhorn Distributionally Robust Optimization

Reference 2024

Resolution: unresolved; no resolver link, observed 2026-08-07T12:45:46.145612Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 05b00824-ee5b-4615-9157-ad26fb409078 · outbound

This paper cites fit_transform ) ( batch ) for batch in batches ) This reduces wall-clock time significantly while keeping memory usage controlled.

DRO: A Python Library for Distributionally Robust Optimization in Machine Learning fit_transform ) ( batch ) for batch in batches ) This reduces wall-clock time significantly while keeping memory usage controlled

Reference 5000

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:45:47.369968Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Pith citing papers

Observation 10181415-8ba9-4ab8-83e6-6c0bfb2c5783 · inbound

Data Heterogeneity Modeling for Trustworthy Machine Learning cites this paper.

Data Heterogeneity Modeling for Trustworthy Machine Learning DRO: A Python Library for Distributionally Robust Optimization in Machine Learning

Reference 2025

Resolution: unresolved; no resolver link, observed 2026-08-07T11:58:38.461206Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6aa562f3-92d3-492c-913e-9234701d8886 · inbound

Unregularized limit of stochastic gradient method for Wasserstein distributionally robust optimization cites this paper.

Unregularized limit of stochastic gradient method for Wasserstein distributionally robust optimization DRO: A Python Library for Distributionally Robust Optimization in Machine Learning

Reference 29

Resolution: verified exact; local_arxiv, observed 2026-08-07T10:40:37.680838Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.