Paper Citation Record · LEDGER

Distributed Learning with Compressed Gradient Differences

As of 20 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 14 inbound Pith citation observations for arXiv:1901.09269.

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

pith.paper-citation-record.v1
1901.09269 v3

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 14 of 14 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-19T06:32:44.657259+00:00

measured 14 of 14 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-15T20:44:56.987520Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-21T05:49:40.712610Z

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 926f2bc9-dce5-4b58-9da9-4ceb8a9bbb07 · inbound

Accelerated Methods with Compressed Communications for Distributed Optimization Problems under Data Similarity cites this paper.

Accelerated Methods with Compressed Communications for Distributed Optimization Problems under Data Similarity Distributed Learning with Compressed Gradient Differences

Reference 36

Resolution: unresolved; no resolver link, observed 2026-08-11T10:48:30.053659Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 93dcd450-89b3-4ddf-9e4a-4a7cabb36874 · inbound

The Stochastic Multi-Proximal Method for Nonsmooth Optimization cites this paper.

The Stochastic Multi-Proximal Method for Nonsmooth Optimization Distributed Learning with Compressed Gradient Differences

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-15T20:44:56.987520Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b049019a-0372-4b05-8cfa-f7cb644f736a · inbound

Event-Driven Online Vertical Federated Learning cites this paper.

Event-Driven Online Vertical Federated Learning Distributed Learning with Compressed Gradient Differences

Reference 39

Resolution: unresolved; no resolver link, observed 2026-08-15T19:57:01.049758Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9d4e5667-3ad4-45e2-b4c5-4edfee898bad · inbound

Beyond Communication Overhead: A Multilevel Monte Carlo Approach for Mitigating Compression Bias in Distributed Learning cites this paper.

Beyond Communication Overhead: A Multilevel Monte Carlo Approach for Mitigating Compression Bias in Distributed Learning Distributed Learning with Compressed Gradient Differences

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-06T19:35:15.337111Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 058ca985-3f8f-484f-a715-8f4815e29f4e · inbound

Quantized Rank Reduction: A Communications-Efficient Federated Learning Scheme for Network-Critical Applications cites this paper.

Quantized Rank Reduction: A Communications-Efficient Federated Learning Scheme for Network-Critical Applications Distributed Learning with Compressed Gradient Differences

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-06T17:19:32.513897Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b006044d-54cc-418d-bdd6-7cf479bb6aef · inbound

Federated Majorize-Minimization: Beyond Parameter Aggregation cites this paper.

Federated Majorize-Minimization: Beyond Parameter Aggregation Distributed Learning with Compressed Gradient Differences

Reference 66

Resolution: unresolved; no resolver link, observed 2026-08-06T14:54:37.077686Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4193532b-7aeb-491d-b65f-be918068dc3b · inbound

Optimization Methods and Software for Federated Learning cites this paper.

Optimization Methods and Software for Federated Learning Distributed Learning with Compressed Gradient Differences

Reference 2019

Resolution: unresolved; no resolver link, observed 2026-08-04T21:20:47.215429Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ee8337e3-0f14-4d8f-b4f5-f0dcaa0e16d2 · inbound

EdgeDetect: Importance-Aware Gradient Compression with Homomorphic Aggregation for Federated Intrusion Detection cites this paper.

EdgeDetect: Importance-Aware Gradient Compression with Homomorphic Aggregation for Federated Intrusion Detection Distributed Learning with Compressed Gradient Differences

Reference 43

Resolution: metadata mismatch; arxiv_id, observed 2026-05-10T11:30:18.963677Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation b60bd406-62ab-468b-9774-9d81a2fa8b74 · inbound

Scalable Distributed Stochastic Optimization via Bidirectional Compression: Beyond Pessimistic Limits cites this paper.

Scalable Distributed Stochastic Optimization via Bidirectional Compression: Beyond Pessimistic Limits Distributed Learning with Compressed Gradient Differences

Reference 19

Resolution: verified exact; arxiv_id, observed 2026-05-11T03:05:54.861564Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 69f1287d-6031-4b31-8fff-d39dfcae1abb · inbound

Rennala MVR: Improved Time Complexity for Parallel Stochastic Optimization via Momentum-Based Variance Reduction cites this paper.

Rennala MVR: Improved Time Complexity for Parallel Stochastic Optimization via Momentum-Based Variance Reduction Distributed Learning with Compressed Gradient Differences

Reference 95

Resolution: verified exact; arxiv_id, observed 2026-05-12T07:51:29.893744Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 5757dc2c-0f63-47b2-89c1-a1d2974dd3da · inbound

Rescaled Asynchronous SGD: Optimal Distributed Optimization under Data and System Heterogeneity cites this paper.

Rescaled Asynchronous SGD: Optimal Distributed Optimization under Data and System Heterogeneity Distributed Learning with Compressed Gradient Differences

Reference 213

Resolution: verified exact; arxiv_id, observed 2026-05-14T19:32:52.115188Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation ce4f0e07-7b67-440d-9fa5-7cef5a2449a6 · inbound

Ringmaster LMO: Asynchronous Linear Minimization Oracle Momentum Method cites this paper.

Ringmaster LMO: Asynchronous Linear Minimization Oracle Momentum Method Distributed Learning with Compressed Gradient Differences

Reference 97

Resolution: verified exact; arxiv_id, observed 2026-05-20T13:13:18.628288Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation f04a6f94-5f30-4392-be56-2c3dd2846d82 · inbound

LOSCAR-SGD: Local SGD with Communication-Computation Overlap and Delay-Corrected Sparse Model Averaging cites this paper.

LOSCAR-SGD: Local SGD with Communication-Computation Overlap and Delay-Corrected Sparse Model Averaging Distributed Learning with Compressed Gradient Differences

Reference 99

Resolution: verified exact; arxiv_id, observed 2026-05-21T05:49:40.714172Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 9f088a6c-90cc-4e24-b4e2-eb56bda42e58 · inbound

Theoretical Foundations of Communication-Efficient, Robust, and Practical Distributed and Federated Optimization cites this paper.

Theoretical Foundations of Communication-Efficient, Robust, and Practical Distributed and Federated Optimization Distributed Learning with Compressed Gradient Differences

Reference 189

Resolution: unresolved; no resolver link, observed 2026-08-15T14:39:14.822912Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.