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Paper Citation Record · LEDGER

Semantic-based Distributed Learning for Diverse and Discriminative Representations

As of 6 August 2026, this Paper Citation Record lists 47 of 47 outbound references and 0 inbound Pith citation observations for arXiv:2604.18237.

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

pith.paper-citation-record.v1
2604.18237 v1

Coverage vector

measured 47 of 47 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-05-10T05:07:23.465515Z

measured 47 of 47 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-06T06:34:29.942622+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

47 of 47 outbound references displayed

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  • verified fuzzy41
  • unresolved0
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 3d6f7e8a-8c3d-4dc2-8c54-ee3a155045ee · outbound

This paper cites Distributed learning in wireless networks: Recent progress and future challenges.

Semantic-based Distributed Learning for Diverse and Discriminative Representations Distributed learning in wireless networks: Recent progress and future challenges

Reference 1

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Observation 5f943025-8bf4-44d2-b885-26aba46f6aff · outbound

This paper cites On the principles of parsimony and self-consistency for the emergence of intelligence.

Semantic-based Distributed Learning for Diverse and Discriminative Representations On the principles of parsimony and self-consistency for the emergence of intelligence

Reference 2

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Observation cf7ffcac-55d8-46a4-9bc1-b2ccb3e5bc30 · outbound

This paper cites A geometric analysis of neural collapse with unconstrained features.

Semantic-based Distributed Learning for Diverse and Discriminative Representations A geometric analysis of neural collapse with unconstrained features

Reference 3

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Observation 875e599e-4169-4948-b85e-ac6ed522902a · outbound

This paper cites Neural collapse with normalized features: A geometric analysis over the riemannian manifold.

Semantic-based Distributed Learning for Diverse and Discriminative Representations Neural collapse with normalized features: A geometric analysis over the riemannian manifold

Reference 4

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No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

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Observation 6f247949-eb6a-409f-8da8-a392d9207ede · outbound

This paper cites A Complexity-Based Theory of Compositionality.

Semantic-based Distributed Learning for Diverse and Discriminative Representations A Complexity-Based Theory of Compositionality

Reference 5

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Observation 1daa209d-120a-4d92-b79e-c0ef12e12997 · outbound

This paper cites Federated learn- ing: Challenges, methods, and future directions.

Semantic-based Distributed Learning for Diverse and Discriminative Representations Federated learn- ing: Challenges, methods, and future directions

Reference 6

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Observation 22097345-c956-4d53-a573-54e7dde77016 · outbound

This paper cites Can decentralized algorithms out- perform centralized algorithms? a case study for decentralized parallel stochastic gradient descent.

Semantic-based Distributed Learning for Diverse and Discriminative Representations Can decentralized algorithms out- perform centralized algorithms? a case study for decentralized parallel stochastic gradient descent

Reference 7

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No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

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Observation 5eb1166c-9d89-47f8-9d25-38a7653b2459 · outbound

This paper cites Federated multi-task learning.

Semantic-based Distributed Learning for Diverse and Discriminative Representations Federated multi-task learning

Reference 8

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Observation 6dd819d4-c8b1-4e08-a0c7-1d31f9e98ded · outbound

This paper cites Distributed stochastic gradient tracking methods.

Semantic-based Distributed Learning for Diverse and Discriminative Representations Distributed stochastic gradient tracking methods

Reference 9

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Observation 5545d2ef-e7d7-4c67-aedc-ece407afa3d0 · outbound

This paper cites Distributed learning over networks with graph-attention-based personaliza- tion.

Semantic-based Distributed Learning for Diverse and Discriminative Representations Distributed learning over networks with graph-attention-based personaliza- tion

Reference 10

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Observation 916f217f-cbf1-410a-b3da-f704078ee8a4 · outbound

This paper cites Robust and communication-efficient federated learning from non-iid data.

Semantic-based Distributed Learning for Diverse and Discriminative Representations Robust and communication-efficient federated learning from non-iid data

Reference 11

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Observation 6b9a16ba-1d69-4176-af03-da12266953e0 · outbound

This paper cites Ex- ploiting shared representations for personalized federated learn- ing.

Semantic-based Distributed Learning for Diverse and Discriminative Representations Ex- ploiting shared representations for personalized federated learn- ing

Reference 12

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Observation 3b75f51d-ca5c-42ae-8267-e490ebc72787 · outbound

This paper cites Distributed compressed sensing with personalized variational auto-encoders.

Semantic-based Distributed Learning for Diverse and Discriminative Representations Distributed compressed sensing with personalized variational auto-encoders

Reference 13

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Observation ae12d7a5-3128-4db1-9d91-361965d185c3 · outbound

This paper cites One-bit over-the-air aggregation for communication-efficient federated edge learning: Design and convergence analysis.

Semantic-based Distributed Learning for Diverse and Discriminative Representations One-bit over-the-air aggregation for communication-efficient federated edge learning: Design and convergence analysis

Reference 14

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No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

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Observation 379b4824-41e2-4acb-86d0-fd7babb77948 · outbound

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

Semantic-based Distributed Learning for Diverse and Discriminative Representations Communication-efficient learning of deep networks from decentralized data

Reference 15

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No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

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Observation b639e617-ac4c-4f80-ada6-8329785e8487 · outbound

This paper cites Communication-efficient federated learning based on compressed sensing.

Semantic-based Distributed Learning for Diverse and Discriminative Representations Communication-efficient federated learning based on compressed sensing

Reference 16

Resolution
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

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Observation 599951a9-891c-4054-9843-a7b8824cb33a · outbound

This paper cites Fed- mask: Joint computation and communication-efficient personal- ized federated learning via heterogeneous masking.

Semantic-based Distributed Learning for Diverse and Discriminative Representations Fed- mask: Joint computation and communication-efficient personal- ized federated learning via heterogeneous masking

Reference 17

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verified fuzzy
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No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

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Observation b03ee966-a0d9-42ce-85f8-cc53cddab804 · outbound

This paper cites Group knowledge transfer: Federated learning of large cnns at the edge.

Semantic-based Distributed Learning for Diverse and Discriminative Representations Group knowledge transfer: Federated learning of large cnns at the edge

Reference 18

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No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

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Observation a1be22e0-a19c-4e04-91db-0711933bc88e · outbound

This paper cites Distributed learning of deep neural network over multiple nodes.

Semantic-based Distributed Learning for Diverse and Discriminative Representations Distributed learning of deep neural network over multiple nodes

Reference 19

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No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

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Observation 7e2a5510-4c4a-4ee9-a8d1-ee82f11a2009 · outbound

This paper cites HeteroFL: Computation and Communication Efficient Federated Learning for Heterogeneous Clients.

Semantic-based Distributed Learning for Diverse and Discriminative Representations HeteroFL: Computation and Communication Efficient Federated Learning for Heterogeneous Clients

Reference 20

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Observation 0c8fa9b1-592e-41ff-b4ac-56a8feb37f91 · outbound

This paper cites Fjord: Fair and accurate federated learning under heterogeneous targets with ordered dropout.

Semantic-based Distributed Learning for Diverse and Discriminative Representations Fjord: Fair and accurate federated learning under heterogeneous targets with ordered dropout

Reference 21

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Observation 9823fec4-5048-4668-b76e-7d172300b4e9 · outbound

This paper cites Tailorfl: Dual-personalized federated learning under system and data heterogeneity.

Semantic-based Distributed Learning for Diverse and Discriminative Representations Tailorfl: Dual-personalized federated learning under system and data heterogeneity

Reference 22

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No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

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Observation 8a308e84-93c5-4f27-b2b0-87eb38e9242c · outbound

This paper cites Model pruning enables efficient federated learning on edge devices.

Semantic-based Distributed Learning for Diverse and Discriminative Representations Model pruning enables efficient federated learning on edge devices

Reference 23

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Observation f4de0ab9-0df0-40e3-b8f6-ee11f89be80a · outbound

This paper cites Communication- Efficient Personalized Distributed Learning with Data and Node Heterogeneity.

Semantic-based Distributed Learning for Diverse and Discriminative Representations Communication- Efficient Personalized Distributed Learning with Data and Node Heterogeneity

Reference 24

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No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

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Observation aba803c4-1940-4e78-b8b2-d23e5b2115b8 · outbound

This paper cites FedHM: Efficient Federated Learning for Heterogeneous Models via Low-rank Factorization.

Semantic-based Distributed Learning for Diverse and Discriminative Representations FedHM: Efficient Federated Learning for Heterogeneous Models via Low-rank Factorization

Reference 25

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No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

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Observation 38a6f28b-eaa9-48ba-952e-c3a0fce2f7d8 · outbound

This paper cites Resource-adaptive federated learning with all-in-one neural composition.

Semantic-based Distributed Learning for Diverse and Discriminative Representations Resource-adaptive federated learning with all-in-one neural composition

Reference 26

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No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

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Observation cb4e0597-d44c-49e9-9a49-2cf7b425b0cc · outbound

This paper cites Deep representation learning: Funda- mentals, technologies, applications, and open challenges.

Semantic-based Distributed Learning for Diverse and Discriminative Representations Deep representation learning: Funda- mentals, technologies, applications, and open challenges

Reference 27

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

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Observation ea84e915-8b62-4017-a232-1ca78f58c5ba · outbound

This paper cites A survey of multi-view represen- tation learning.

Semantic-based Distributed Learning for Diverse and Discriminative Representations A survey of multi-view represen- tation learning

Reference 28

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

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Observation 5fe3c16c-58c2-4ded-9e53-081209cfed4a · outbound

This paper cites Representation learn- ing: A review and new perspectives.

Semantic-based Distributed Learning for Diverse and Discriminative Representations Representation learn- ing: A review and new perspectives

Reference 29

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verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

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Observation 44d3aa1a-4faf-4d40-bb5d-e3892324bd6e · outbound

This paper cites Distributed representation learning via node2vec for implicit feedback rec- ommendation.

Semantic-based Distributed Learning for Diverse and Discriminative Representations Distributed representation learning via node2vec for implicit feedback rec- ommendation

Reference 30

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

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Observation 20a691d2-2a66-4170-b2e8-2971e44be05a · outbound

This paper cites Distributed variational represen- tation learning.

Semantic-based Distributed Learning for Diverse and Discriminative Representations Distributed variational represen- tation learning

Reference 31

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

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Observation dfbf6de9-58dd-4520-960e-12f6b090375d · outbound

This paper cites Collaborative unsupervised visual representation learning from decentralized data.

Semantic-based Distributed Learning for Diverse and Discriminative Representations Collaborative unsupervised visual representation learning from decentralized data

Reference 32

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

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Observation 978ff8a9-a129-43ac-b04c-1da42d723220 · outbound

This paper cites Orchestra: Unsupervised Federated Learning via Globally Consistent Clustering.

Semantic-based Distributed Learning for Diverse and Discriminative Representations Orchestra: Unsupervised Federated Learning via Globally Consistent Clustering

Reference 33

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arxiv_id, observed 2026-05-10T09:48:47.997591Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

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Observation 3aa74724-40d1-45e8-b99d-0e52b44d9c69 · outbound

This paper cites Rethinking the representation in federated unsupervised learning with non-iid data.

Semantic-based Distributed Learning for Diverse and Discriminative Representations Rethinking the representation in federated unsupervised learning with non-iid data

Reference 34

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raw_fallback, observed 2026-05-21T23:45:47.655094Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-05-10T05:07:23.465515Z digest=sha256:a0e16ac222f061a2009437ba98126b6f49085bed7dd7e32fac0e5d7a3482d5c3

Observation 5e137c45-d875-4618-aa2d-8741ebae49ca · outbound

This paper cites Federated unsupervised representation learning.

Semantic-based Distributed Learning for Diverse and Discriminative Representations Federated unsupervised representation learning

Reference 35

Resolution
verified fuzzy
raw_fallback, observed 2026-05-21T23:45:47.720032Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-05-10T05:07:23.465515Z digest=sha256:84a93701341812d82e05310f3cc555026c612b0bff65327459a67be6cce2fe6d

Observation c9afcf8c-255f-4bdd-bad7-abfc4c1e15a6 · outbound

This paper cites Simclr: A simple framework for contrastive learning of visual representa- tions.

Semantic-based Distributed Learning for Diverse and Discriminative Representations Simclr: A simple framework for contrastive learning of visual representa- tions

Reference 36

Resolution
verified fuzzy
raw_fallback, observed 2026-05-21T23:45:47.739591Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-05-10T05:07:23.465515Z digest=sha256:4c143169f9f581ece3fe9e484b6d36cd90d5c8a2826414d5065e7ec46578a425

Observation fca97b65-2dde-486f-8a4b-73849bc9aad6 · outbound

This paper cites SheafAlign: A Sheaf-theoretic Framework for Decentralized Multimodal Alignment.

Semantic-based Distributed Learning for Diverse and Discriminative Representations SheafAlign: A Sheaf-theoretic Framework for Decentralized Multimodal Alignment

Reference 37

Resolution
verified exact
arxiv_id, observed 2026-05-10T09:48:48.010608Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-05-10T05:07:23.465515Z digest=sha256:7fbf53276268080115b40fbf0db51940319f1de62ce970541e8d80f48e888b8a

Observation 4458a7e2-1d5f-42d9-9626-5040dbcdd77f · outbound

This paper cites Learning diverse and discriminative representations via the principle of maximal coding rate reduction.

Semantic-based Distributed Learning for Diverse and Discriminative Representations Learning diverse and discriminative representations via the principle of maximal coding rate reduction

Reference 38

Resolution
verified fuzzy
raw_fallback, observed 2026-05-21T23:45:47.723181Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-05-10T05:07:23.465515Z digest=sha256:66131194cabe11c157467fa6b2faa26a1f4d75c4c1adf3c226f9360d9961cc4d

Observation 01f576e1-73c5-4d69-9f86-580b9d90312d · outbound

This paper cites Closed-Loop Data Transcription to an LDR via Minimaxing Rate Reduction.

Semantic-based Distributed Learning for Diverse and Discriminative Representations Closed-Loop Data Transcription to an LDR via Minimaxing Rate Reduction

Reference 39

Resolution
verified exact
arxiv_id, observed 2026-05-10T09:48:48.003557Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-05-10T05:07:23.465515Z digest=sha256:5f67505d4090f98a41f738635458e1e0e278019d3f492d651b91c2e7cb1beb88

Observation b293ffbb-c5d4-4176-ab93-700b457ccbc6 · outbound

This paper cites Compositional Distributed Learning for Multi-View Perception: A Maximal Coding Rate Reduction Perspective.

Semantic-based Distributed Learning for Diverse and Discriminative Representations Compositional Distributed Learning for Multi-View Perception: A Maximal Coding Rate Reduction Perspective

Reference 40

Resolution
verified fuzzy
raw_fallback, observed 2026-05-21T23:45:47.729085Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-05-10T05:07:23.465515Z digest=sha256:b9050801a67e757b1572738a336ea04e61a6c6f56f38b78d70dfccf105924ce2

Observation 91cf5fbe-00d0-4333-993e-50c076c09eb7 · outbound

This paper cites Segmentation of multivariate mixed data via lossy data coding and compression.

Semantic-based Distributed Learning for Diverse and Discriminative Representations Segmentation of multivariate mixed data via lossy data coding and compression

Reference 41

Resolution
verified fuzzy
raw_fallback, observed 2026-05-21T23:45:47.731914Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-05-10T05:07:23.465515Z digest=sha256:fbdc6ba047c63c59eb4dfbb130e843a563ecbe5a7e4528cf179e6f814a689b0b

Observation 5a5aaf85-2b5e-405c-ab1f-0926229aa650 · outbound

This paper cites Distributed admm with synergetic communication and compu- tation.

Semantic-based Distributed Learning for Diverse and Discriminative Representations Distributed admm with synergetic communication and compu- tation

Reference 42

Resolution
verified fuzzy
raw_fallback, observed 2026-05-21T23:45:47.734432Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-05-10T05:07:23.465515Z digest=sha256:a83fefeea3ed5371f9621d289862975dd9429e22bfc9d5dab48702aa145393c5

Observation 8dff7f92-f92a-49c2-b12f-14eadad8decd · outbound

This paper cites Distributed admm for in-network reconstruction of sparse sig- nals with innovations.

Semantic-based Distributed Learning for Diverse and Discriminative Representations Distributed admm for in-network reconstruction of sparse sig- nals with innovations

Reference 43

Resolution
verified fuzzy
raw_fallback, observed 2026-05-21T23:45:47.629990Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-05-10T05:07:23.465515Z digest=sha256:eac9f892b51696e43b6be6cfc1b24f1403c90e528de2e0ec3463be52375da180

Observation 7d0be792-4787-4b3c-9dda-eb76f97e583b · outbound

This paper cites On the linear convergence of the alternating direction method of multipliers.

Semantic-based Distributed Learning for Diverse and Discriminative Representations On the linear convergence of the alternating direction method of multipliers

Reference 44

Resolution
verified fuzzy
raw_fallback, observed 2026-05-21T23:45:47.690203Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-05-10T05:07:23.465515Z digest=sha256:ecca87ef58345ce863d66994ea1cc796dd2f649d5d84581d221ccbc3178b38fa

Observation cc2f0e6a-83f6-4943-bce5-2d15e456ff73 · outbound

This paper cites Distributed multi-view sparse vector recovery.

Semantic-based Distributed Learning for Diverse and Discriminative Representations Distributed multi-view sparse vector recovery

Reference 45

Resolution
verified fuzzy
raw_fallback, observed 2026-05-21T23:45:47.633220Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-05-10T05:07:23.465515Z digest=sha256:8954df221c42d39c39b511dd8e498b8e9e836d8f1c76e83a0274de04116db79a

Observation 3881e50c-a5b8-48e6-af18-548edde6e375 · outbound

This paper cites On the convergence of block coordinate descent type methods.

Semantic-based Distributed Learning for Diverse and Discriminative Representations On the convergence of block coordinate descent type methods

Reference 46

Resolution
verified fuzzy
raw_fallback, observed 2026-05-21T23:45:47.639280Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-05-10T05:07:23.465515Z digest=sha256:6c5e9601740f79a994797c1ed904efe87276eed54acc0f7ea260e6740541d88b

Observation a05bcf7c-a569-491a-82ee-9d896c02a6ee · outbound

This paper cites Iteration complexity analysis of block coordinate descent methods.

Semantic-based Distributed Learning for Diverse and Discriminative Representations Iteration complexity analysis of block coordinate descent methods

Reference 47

Resolution
verified fuzzy
raw_fallback, observed 2026-05-21T23:45:47.627394Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-05-10T05:07:23.465515Z digest=sha256:549c37b8a4b1f5c957c756f281b59baabb158bb4fe8c170c2d8681c16cfdbd8c

Pith citing papers

No inbound Pith citation observations are available.