Paper Citation Record · LEDGER

Learn to Intervene: An Adaptive Learning Policy for Restless Bandits in Application to Preventive Healthcare

As of 11 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 6 inbound Pith citation observations for arXiv:2105.07965.

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

pith.paper-citation-record.v1
2105.07965 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 6 of 6 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-11T06:34:44.6726+00:00

measured 6 of 6 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-05T20:27:03.273298Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-23T03:22:28.006972Z

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 ef518dae-b2c5-4289-9480-87b26183fcd1 · inbound

From Restless to Contextual: A Thresholding Bandit Reformulation For Finite-horizon Improvement cites this paper.

From Restless to Contextual: A Thresholding Bandit Reformulation For Finite-horizon Improvement Learn to Intervene: An Adaptive Learning Policy for Restless Bandits in Application to Preventive Healthcare

Reference 6

Resolution: verified exact; arxiv_id, observed 2026-05-23T03:22:28.010450Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 4bbbaefe-c270-48e2-97e2-ed183797ac63 · inbound

Online Learning of Whittle Indices for Restless Bandits with Non-Stationary Transition Kernels cites this paper.

Online Learning of Whittle Indices for Restless Bandits with Non-Stationary Transition Kernels Learn to Intervene: An Adaptive Learning Policy for Restless Bandits in Application to Preventive Healthcare

Reference 27

Resolution: verified exact; arxiv_id, observed 2026-05-19T07:57:09.949861Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation f69f6a6f-b8de-421c-a133-d25ac6296dcc · inbound

Non-Stationary Restless Multi-Armed Bandits with Provable Guarantee cites this paper.

Non-Stationary Restless Multi-Armed Bandits with Provable Guarantee Learn to Intervene: An Adaptive Learning Policy for Restless Bandits in Application to Preventive Healthcare

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-05T20:27:03.273298Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d8fafbc1-41fc-4b45-b524-8c283b3c446a · inbound

Optimizing Resource-Constrained Non-Pharmaceutical Interventions for Multi-Cluster Outbreak Control Using Hierarchical Reinforcement Learning cites this paper.

Optimizing Resource-Constrained Non-Pharmaceutical Interventions for Multi-Cluster Outbreak Control Using Hierarchical Reinforcement Learning Learn to Intervene: An Adaptive Learning Policy for Restless Bandits in Application to Preventive Healthcare

Reference 7

Resolution: verified exact; arxiv_id, observed 2026-05-15T07:59:50.753133Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation b9a8a678-118a-421b-aa27-ac5cc1b1f646 · inbound

Fair and Efficient Scheduling for Sensor Networks via Online Whittle Index Policy cites this paper.

Fair and Efficient Scheduling for Sensor Networks via Online Whittle Index Policy Learn to Intervene: An Adaptive Learning Policy for Restless Bandits in Application to Preventive Healthcare

Reference 48

Resolution: verified exact; arxiv_id, observed 2026-05-12T08:31:23.639227Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 2f7ec48c-8345-47ef-ac38-855769c5fcec · inbound

Fair and Efficient Scheduling for Sensor Networks via Online Whittle Index Policy cites this paper.

Fair and Efficient Scheduling for Sensor Networks via Online Whittle Index Policy Learn to Intervene: An Adaptive Learning Policy for Restless Bandits in Application to Preventive Healthcare

Reference 48

Resolution: verified exact; arxiv_id, observed 2026-05-21T09:19:56.682602Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.