Paper Citation Record · LEDGER

Fast rates for empirical risk minimization over c\`adl\`ag functions with bounded sectional variation norm

As of 22 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 8 inbound Pith citation observations for arXiv:1907.09244.

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

pith.paper-citation-record.v1
1907.09244 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 8 of 8 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-22T06:32:14.747728+00:00

measured 8 of 8 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-15T19:15:34.905936Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-06-30T17:54:58.126444Z

Reference resolution

0 of 0 outbound references displayed

verified exact0
verified fuzzy0
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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 1e23951c-9ce7-4762-8e03-a682dda75c17 · inbound

Double Reinforcement Learning for Efficient Off-Policy Evaluation in Markov Decision Processes cites this paper.

Double Reinforcement Learning for Efficient Off-Policy Evaluation in Markov Decision Processes Fast rates for empirical risk minimization over c\`adl\`ag functions with bounded sectional variation norm

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-14T11:46:29.690268Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ac0c2e69-843e-4432-863b-aae5a09815c4 · inbound

An Online Meta-Level Adaptive Design Framework with Targeted Learning Inference: Applications to Evaluating and Utilizing Surrogate Outcomes in Adaptive Designs cites this paper.

An Online Meta-Level Adaptive Design Framework with Targeted Learning Inference: Applications to Evaluating and Utilizing Surrogate Outcomes in Adaptive Designs Fast rates for empirical risk minimization over c\`adl\`ag functions with bounded sectional variation norm

Reference 4

Resolution: verified exact; arxiv_id, observed 2026-05-23T22:03:30.564461Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 4d4c4bc3-5bb1-49eb-bbf9-a754031d4345 · inbound

Regularized Targeted Maximum Likelihood Estimation in Highly Adaptive Lasso Implied Working Models cites this paper.

Regularized Targeted Maximum Likelihood Estimation in Highly Adaptive Lasso Implied Working Models Fast rates for empirical risk minimization over c\`adl\`ag functions with bounded sectional variation norm

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-15T19:15:34.905936Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ff0bc0d2-f2d3-4701-8e26-66dd10c89e37 · inbound

Fitted $Q$ Evaluation Without Bellman Completeness via Stationary Weighting cites this paper.

Fitted $Q$ Evaluation Without Bellman Completeness via Stationary Weighting Fast rates for empirical risk minimization over c\`adl\`ag functions with bounded sectional variation norm

Reference 4

Resolution: verified exact; arxiv_id, observed 2026-05-16T19:08:19.131550Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 82b1139c-fd62-4e64-9930-ac42e972ff82 · inbound

Stationary Reweighting Yields Local Convergence of Soft Fitted Q-Iteration cites this paper.

Stationary Reweighting Yields Local Convergence of Soft Fitted Q-Iteration Fast rates for empirical risk minimization over c\`adl\`ag functions with bounded sectional variation norm

Reference 4

Resolution: verified exact; arxiv_id, observed 2026-05-16T19:58:23.635433Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation be8918f0-2fc8-4524-8411-a8576554475d · inbound

Calibeating Prediction-Powered Inference cites this paper.

Calibeating Prediction-Powered Inference Fast rates for empirical risk minimization over c\`adl\`ag functions with bounded sectional variation norm

Reference 3

Resolution: verified exact; arxiv_id, observed 2026-05-11T15:21:10.905136Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation c83c7a2a-30c2-499e-907d-6da29c419d09 · inbound

Evaluating causal indirect effects when mediators are left-censored by assay limit of quantification cites this paper.

Evaluating causal indirect effects when mediators are left-censored by assay limit of quantification Fast rates for empirical risk minimization over c\`adl\`ag functions with bounded sectional variation norm

Reference 54

Resolution: verified exact; arxiv_id, observed 2026-05-21T03:23:55.785904Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation afacd664-9a65-4aa8-9006-ba413d67f540 · inbound

Evaluating causal indirect effects when mediators are left-censored by assay limit of quantification cites this paper.

Reference 72

Resolution: verified exact; arxiv_id, observed 2026-06-30T17:54:58.127757Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.