Paper Citation Record · LEDGER

Non-convex composite federated learning with heterogeneous data

As of 19 August 2026, this Paper Citation Record lists 35 of 35 outbound references and 1 inbound Pith citation observation for arXiv:2502.03958.

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

pith.paper-citation-record.v1
2502.03958 v1

Coverage vector

measured 35 of 35 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-09T00:13:44.715349Z

measured 36 of 36 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 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-05-07T16:45:53.627922Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-11T23:31:17.598377Z

Reference resolution

35 of 35 outbound references displayed

verified exact1
verified fuzzy29
unresolved5
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 658092da-76ff-49d0-83d4-4b44473a0e2b · outbound

This paper cites Privacy-preserving and communication-efficient energy prediction scheme based on federated learning for smart grids.

Non-convex composite federated learning with heterogeneous data Privacy-preserving and communication-efficient energy prediction scheme based on federated learning for smart grids

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T00:13:45.767645Z

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 637bd418-395f-454f-ba6a-727fe14e9e3e · outbound

This paper cites Fast composite optimization and statistical recovery in federated learning.

Non-convex composite federated learning with heterogeneous data Fast composite optimization and statistical recovery in federated learning

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T00:13:45.753072Z

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 ebb1316e-0dee-46d7-93a2-aca82a88caa0 · outbound

This paper cites A fast iterative shrinkage- thresholding algorithm for linear inverse problems.

Non-convex composite federated learning with heterogeneous data A fast iterative shrinkage- thresholding algorithm for linear inverse problems

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-09T00:13:44.376019Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 90839fe7-70ee-4484-bcb6-7ed27621eb55 · outbound

This paper cites Online optimization of switched LTI systems using continuous-time and hybrid accelerated gradient flows.

Non-convex composite federated learning with heterogeneous data Online optimization of switched LTI systems using continuous-time and hybrid accelerated gradient flows

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T00:13:45.624780Z

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 59e75279-c566-462d-b74a-40a6c179f22f · outbound

This paper cites Sparse linear regression from perturbed data.

Non-convex composite federated learning with heterogeneous data Sparse linear regression from perturbed data

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T00:13:45.610469Z

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 0d9240b8-7ee1-4198-be6f-b17e2f721632 · outbound

This paper cites Distributed networked real-time learning.

Non-convex composite federated learning with heterogeneous data Distributed networked real-time learning

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T00:13:45.595997Z

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 05cb3c08-afdd-4391-874b-5b8b65751231 · outbound

This paper cites Mini- batch stochastic approximation methods for nonconvex stochastic composite optimization.

Non-convex composite federated learning with heterogeneous data Mini- batch stochastic approximation methods for nonconvex stochastic composite optimization

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-09T00:13:44.453081Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 57f0dbe5-4ec9-463b-b5b0-34628cda1b1c · outbound

This paper cites A strictly contractive Peaceman–Rachford splitting method for convex programming.

Non-convex composite federated learning with heterogeneous data A strictly contractive Peaceman–Rachford splitting method for convex programming

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T00:13:45.571808Z

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 19dbe7b7-d585-400c-a002-24bf6b055280 · outbound

This paper cites Distributed networked learning with correlated data.

Non-convex composite federated learning with heterogeneous data Distributed networked learning with correlated data

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T00:13:45.557618Z

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 c4bcddcd-fa26-486c-8edd-daf268c4ff3b · outbound

This paper cites Proximal stochastic methods for nonsmooth nonconvex finite-sum optimization.

Non-convex composite federated learning with heterogeneous data Proximal stochastic methods for nonsmooth nonconvex finite-sum optimization

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T00:13:45.466054Z

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 ce9b5f3b-169e-4332-b741-382b13416b7a · outbound

This paper cites Linear convergence of gradient and proximal-gradient methods under the Polyak- Lojasiewicz condition.

Non-convex composite federated learning with heterogeneous data Linear convergence of gradient and proximal-gradient methods under the Polyak- Lojasiewicz condition

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T00:13:45.354285Z

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 508eb73e-2bc2-47fa-87f1-34c61b29b067 · outbound

This paper cites Mime: Mimicking Centralized Stochastic Algorithms in Federated Learning.

Non-convex composite federated learning with heterogeneous data Mime: Mimicking Centralized Stochastic Algorithms in Federated Learning

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-09T00:13:44.474773Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3cba474c-68aa-402c-ac68-228c7e491348 · outbound

This paper cites Scaffold: Stochastic controlled averaging for federated learning.

Non-convex composite federated learning with heterogeneous data Scaffold: Stochastic controlled averaging for federated learning

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T00:13:45.301635Z

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 d287e0cc-5f1a-48cc-b9d2-ee6baf8b64c3 · outbound

This paper cites Understanding notions of stationarity in nonsmooth optimization: A guided tour of various constructions of subdifferential for nonsmooth functions.

Non-convex composite federated learning with heterogeneous data Understanding notions of stationarity in nonsmooth optimization: A guided tour of various constructions of subdifferential for nonsmooth functions

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T00:13:45.288299Z

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 971947f8-812d-48d0-8be1-4da76056af6d · outbound

This paper cites Federated optimization in heterogeneous networks.

Non-convex composite federated learning with heterogeneous data Federated optimization in heterogeneous networks

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T00:13:45.274731Z

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 df9b9821-6837-4115-8396-11e8f34fc536 · outbound

This paper cites On the convergence of FedAvg on non-iid data.

Non-convex composite federated learning with heterogeneous data On the convergence of FedAvg on non-iid data

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T00:13:45.261044Z

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 39c7b3c1-28e4-4ff7-98b7-f63028902ecd · outbound

This paper cites Private non-convex federated learning without a trusted server.

Non-convex composite federated learning with heterogeneous data Private non-convex federated learning without a trusted server

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T00:13:45.247646Z

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 3d259f7c-3ca0-456d-9d9b-f65d2ed90384 · outbound

This paper cites Error bounds and convergence analysis of feasible descent methods: a general approach.

Non-convex composite federated learning with heterogeneous data Error bounds and convergence analysis of feasible descent methods: a general approach

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-09T00:13:44.500512Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5f60a6ae-d5b4-4b1d-9061-58ac032afcea · outbound

This paper cites Communication- efficient learning of deep networks from decentralized data.

Non-convex composite federated learning with heterogeneous data Communication- efficient learning of deep networks from decentralized data

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T00:13:45.224836Z

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 1125c4c6-9be6-490b-92e1-f0ddafd287db · outbound

This paper cites Gradient free cooperative seeking of a moving source.

Non-convex composite federated learning with heterogeneous data Gradient free cooperative seeking of a moving source

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T00:13:45.211563Z

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 00b07d0a-cedc-47a7-bc87-40840df2ded2 · outbound

This paper cites Primal-dual subgradient methods for convex problems.

Non-convex composite federated learning with heterogeneous data Primal-dual subgradient methods for convex problems

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T00:13:45.198144Z

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 a98d0910-2f4c-479e-b198-5824c420dd92 · outbound

This paper cites Differentially private federated learning on heterogeneous data.

Non-convex composite federated learning with heterogeneous data Differentially private federated learning on heterogeneous data

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T00:13:45.182916Z

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 3ffb3126-e0e5-4ba9-90d0-f0f50997712e · outbound

This paper cites FedSplit: An algorithmic framework for fast federated optimization.

Non-convex composite federated learning with heterogeneous data FedSplit: An algorithmic framework for fast federated optimization

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T00:13:45.165644Z

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 450285ef-c433-43f2-af04-00220ebc4447 · outbound

This paper cites Local SGD converges fast and communicates little.

Non-convex composite federated learning with heterogeneous data Local SGD converges fast and communicates little

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T00:13:45.130040Z

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 69a438fe-33dc-4d34-a87e-7b5a78be1c57 · outbound

This paper cites FedDR–randomized Douglas-Rachford splitting algorithms for nonconvex federated composite optimization.

Non-convex composite federated learning with heterogeneous data FedDR–randomized Douglas-Rachford splitting algorithms for nonconvex federated composite optimization

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T00:13:45.052239Z

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 b6bdb73c-d54e-461b-bf58-5a58d72874f2 · outbound

This paper cites FedADMM: A federated primal-dual algorithm allowing partial participation.

Non-convex composite federated learning with heterogeneous data FedADMM: A federated primal-dual algorithm allowing partial participation

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T00:13:44.972740Z

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 600ea79b-8ff4-4d73-ad8e-ac93ce49ae9f · outbound

This paper cites Decentralized nonconvex optimization with guaranteed privacy and accuracy.

Non-convex composite federated learning with heterogeneous data Decentralized nonconvex optimization with guaranteed privacy and accuracy

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T00:13:44.922667Z

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 bc41d7a9-e468-49ff-9812-d8657b02de01 · outbound

This paper cites On stochastic gradient and subgradient methods with adaptive steplength sequences.

Non-convex composite federated learning with heterogeneous data On stochastic gradient and subgradient methods with adaptive steplength sequences

Reference 28

Resolution: unresolved; no resolver link, observed 2026-08-09T00:13:44.543212Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2a9be6b5-d13f-49fd-b150-b4c29d04535b · outbound

This paper cites Federated composite optimization.

Non-convex composite federated learning with heterogeneous data Federated composite optimization

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T00:13:44.899341Z

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 209f087d-6c86-43d8-852e-92a1a622fb4b · outbound

This paper cites On convergence of FedProx: Local dissimilarity invariant bounds, non-smoothness and beyond.

Non-convex composite federated learning with heterogeneous data On convergence of FedProx: Local dissimilarity invariant bounds, non-smoothness and beyond

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T00:13:44.884765Z

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 a42a7844-26da-4314-a8ce-1b3d6a322e6f · outbound

This paper cites A family of inexact SQA methods for non-smooth convex minimization with provable convergence guarantees based on the Luo–Tseng error bound property.

Non-convex composite federated learning with heterogeneous data A family of inexact SQA methods for non-smooth convex minimization with provable convergence guarantees based on the Luo–Tseng error bound property

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T00:13:44.871029Z

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 edb25e29-0be7-440d-9841-3674abc0d2f2 · outbound

This paper cites Secure and decentralized federated learning framework with non-iid data based on blockchain.

Non-convex composite federated learning with heterogeneous data Secure and decentralized federated learning framework with non-iid data based on blockchain

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T00:13:44.857205Z

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 0cdffba4-1911-43c5-8dab-b18ef72019b7 · outbound

This paper cites Composite federated learning with heterogeneous data.

Non-convex composite federated learning with heterogeneous data Composite federated learning with heterogeneous data

Reference 33

Resolution: verified exact; local_arxiv, observed 2026-08-09T00:13:44.797770Z

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 79ca0553-7448-47a1-8bf6-7a6c78fa8014 · outbound

This paper cites Fedaudio: A federated learning benchmark for audio tasks.

Non-convex composite federated learning with heterogeneous data Fedaudio: A federated learning benchmark for audio tasks

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T00:13:44.843402Z

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 038bfac5-927b-4d0c-b6d6-4cb69464c6ae · outbound

This paper cites FedPD: A federated learning framework with adaptivity to non-iid data.

Non-convex composite federated learning with heterogeneous data FedPD: A federated learning framework with adaptivity to non-iid data

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T00:13:44.829429Z

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.

Pith citing papers

Observation 1a877e1e-b89c-41cb-adce-16f4c632a498 · inbound

Subspace Optimization for Efficient Federated Learning under Heterogeneous Data cites this paper.

Subspace Optimization for Efficient Federated Learning under Heterogeneous Data Non-convex composite federated learning with heterogeneous data

Reference 30

Resolution: verified exact; arxiv_id, observed 2026-05-11T23:31:17.605124Z

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.