Paper Citation Record · LEDGER

Noise-Resistant Label Reconstruction Feature Selection for Partial Multi-Label Learning

As of 8 August 2026, this Paper Citation Record lists 39 of 39 outbound references and 0 inbound Pith citation observations for arXiv:2506.04669.

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

pith.paper-citation-record.v1
2506.04669 v1

Coverage vector

measured 39 of 39 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T10:42:33.343426Z

measured 39 of 39 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+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

39 of 39 outbound references displayed

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verified fuzzy38
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation d2cd781c-daf8-4140-9ef4-11be9608facd · outbound

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

Noise-Resistant Label Reconstruction Feature Selection for Partial Multi-Label Learning A fast iterative shrinkage-thresholding algorithm for lin- ear inverse problems

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:42:35.248974Z

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Observation f1c556f8-83ac-4938-b762-f6dce8f4e889 · outbound

This paper cites Partial multi-label learning via multi-subspace represen- tation.

Noise-Resistant Label Reconstruction Feature Selection for Partial Multi-Label Learning Partial multi-label learning via multi-subspace represen- tation

Reference 13

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Observation 2c6664cc-c421-4448-944d-b478fde5b938 · outbound

This paper cites Multi-label feature selection with high-sparse personalized and low-redundancy shared common features.Information Processing & Management, 61(3):103633,.

Noise-Resistant Label Reconstruction Feature Selection for Partial Multi-Label Learning Multi-label feature selection with high-sparse personalized and low-redundancy shared common features.Information Processing & Management, 61(3):103633,

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:42:34.775869Z

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Observation a901111c-8215-4337-b48d-27d82ee82c2a · outbound

This paper cites The emerging trends of multi-label learning.

Noise-Resistant Label Reconstruction Feature Selection for Partial Multi-Label Learning The emerging trends of multi-label learning

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:42:34.602826Z

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Observation 4b8bbd96-73e1-4646-86fe-07dbf8427b4e · outbound

This paper cites Efficient and robust feature selection via joint l2, 1-norms minimization.

Noise-Resistant Label Reconstruction Feature Selection for Partial Multi-Label Learning Efficient and robust feature selection via joint l2, 1-norms minimization

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:42:34.573687Z

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Observation b31ebd87-3e29-4ffa-b55c-2206f3f58589 · outbound

This paper cites Random forest.

Noise-Resistant Label Reconstruction Feature Selection for Partial Multi-Label Learning Random forest

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:42:34.399933Z

Source-reported events for the cited work

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Observation 4598d98a-8b27-4699-92d5-2c25b940cdc1 · outbound

This paper cites Partial multi-label learning by low-rank and sparse decomposition.

Noise-Resistant Label Reconstruction Feature Selection for Partial Multi-Label Learning Partial multi-label learning by low-rank and sparse decomposition

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:42:34.285081Z

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Observation 9969014a-6726-43f5-bd26-384914316f5f · outbound

This paper cites Semantic annota- tion and retrieval of music and sound effects.

Noise-Resistant Label Reconstruction Feature Selection for Partial Multi-Label Learning Semantic annota- tion and retrieval of music and sound effects

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:42:34.235749Z

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Observation 7bb788c7-e605-43d8-b3cd-28de79c283b0 · outbound

This paper cites Deep multi-view subspace clustering with unified and dis- criminative learning.

Noise-Resistant Label Reconstruction Feature Selection for Partial Multi-Label Learning Deep multi-view subspace clustering with unified and dis- criminative learning

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:42:34.084512Z

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No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 6ea16f9f-6b02-4ccd-b95c-8a7347954c8e · outbound

This paper cites Partial multi-label learning.

Noise-Resistant Label Reconstruction Feature Selection for Partial Multi-Label Learning Partial multi-label learning

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:42:34.047475Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation f0dc64e8-177c-4e2a-a0a6-e682c97ad9ff · outbound

This paper cites Partial multi-label learning with noisy label identification.

Noise-Resistant Label Reconstruction Feature Selection for Partial Multi-Label Learning Partial multi-label learning with noisy label identification

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:42:33.955673Z

Source-reported events for the cited work

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Observation 922a1d0f-76a2-4ca5-9d77-6a56a6919fae · outbound

This paper cites Robust extreme multi-label learning.

Noise-Resistant Label Reconstruction Feature Selection for Partial Multi-Label Learning Robust extreme multi-label learning

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:42:33.891357Z

Source-reported events for the cited work

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Observation 7260608f-0ddb-4364-a722-03a4feb43fae · outbound

This paper cites Partial multi-label learning with label distribution.

Noise-Resistant Label Reconstruction Feature Selection for Partial Multi-Label Learning Partial multi-label learning with label distribution

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:42:33.860028Z

Source-reported events for the cited work

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Observation e69ab4b1-7656-4ef7-a66a-fc1db807e18f · outbound

This paper cites Multi-label sentiment analysis on 100 languages with dynamic weighting for label imbalance.

Noise-Resistant Label Reconstruction Feature Selection for Partial Multi-Label Learning Multi-label sentiment analysis on 100 languages with dynamic weighting for label imbalance

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:42:33.818077Z

Source-reported events for the cited work

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Observation 08afdb82-561d-44a1-9343-eb84a441f892 · outbound

This paper cites Feature-induced partial multi-label learning.

Noise-Resistant Label Reconstruction Feature Selection for Partial Multi-Label Learning Feature-induced partial multi-label learning

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:42:33.765459Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 6a445502-098f-4e96-b458-92ca81766b9d · outbound

This paper cites Partial multi-label learning with label and feature collaboration.

Noise-Resistant Label Reconstruction Feature Selection for Partial Multi-Label Learning Partial multi-label learning with label and feature collaboration

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:42:33.723924Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation cd42a5e9-4206-45b5-be0c-6d3b2584584c · outbound

This paper cites Partial multi-label learning via credible label elicita- tion.

Noise-Resistant Label Reconstruction Feature Selection for Partial Multi-Label Learning Partial multi-label learning via credible label elicita- tion

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:42:33.619377Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation e1d63ba2-3066-4e3c-acd4-22c31af3940e · outbound

This paper cites Feature relevance term variation for multi-label feature selection.

Noise-Resistant Label Reconstruction Feature Selection for Partial Multi-Label Learning Feature relevance term variation for multi-label feature selection

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:42:33.573340Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 94da8a3f-69a3-4098-82e5-6d8c53db6b78 · outbound

This paper cites Ml-knn: A lazy learning approach to multi-label learning.

Noise-Resistant Label Reconstruction Feature Selection for Partial Multi-Label Learning Ml-knn: A lazy learning approach to multi-label learning

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:42:33.539834Z

Source-reported events for the cited work

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Observation 745f5103-9ad1-4d3e-b831-8782f13d99ac · outbound

This paper cites Feature selection based on mutual infor- mation with correlation coefficient.

Noise-Resistant Label Reconstruction Feature Selection for Partial Multi-Label Learning Feature selection based on mutual infor- mation with correlation coefficient

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:42:33.496035Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 17945985-2562-4401-b2f4-9de5300116ef · outbound

This paper cites Symptom selection for multi-label data of inquiry diagnosis in traditional chinese medicine.

Noise-Resistant Label Reconstruction Feature Selection for Partial Multi-Label Learning Symptom selection for multi-label data of inquiry diagnosis in traditional chinese medicine

Reference 1948

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:42:34.326445Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 575c721e-e003-4797-a934-f94b25354824 · outbound

This paper cites The 9th annual mlsp compe- tition: New methods for acoustic classification of multiple simultaneous bird species in a noisy environment.

Noise-Resistant Label Reconstruction Feature Selection for Partial Multi-Label Learning The 9th annual mlsp compe- tition: New methods for acoustic classification of multiple simultaneous bird species in a noisy environment

Reference 1999

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:42:35.149189Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 61c8b842-3c7c-48c0-8c8b-2ebc466c658b · outbound

This paper cites Class-specific mutual information variation for feature se- lection.

Noise-Resistant Label Reconstruction Feature Selection for Partial Multi-Label Learning Class-specific mutual information variation for feature se- lection

Reference 2001

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:42:34.984429Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 783f4cec-e538-4959-9b13-217f1ed1f9e5 · outbound

This paper cites A kernel method for multi-labelled classification.

Noise-Resistant Label Reconstruction Feature Selection for Partial Multi-Label Learning A kernel method for multi-labelled classification

Reference 2002

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:42:35.007467Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 4ef7b547-bbbe-4d60-aa31-bace65653422 · outbound

This paper cites Low-rank multi-view learning in matrix completion for multi-label image classification.

Noise-Resistant Label Reconstruction Feature Selection for Partial Multi-Label Learning Low-rank multi-view learning in matrix completion for multi-label image classification

Reference 2006

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:42:34.650614Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation a98fb551-fd8c-4654-9437-34271301c8d4 · outbound

This paper cites Discrimina- tive and correlative partial multi-label learning.

Noise-Resistant Label Reconstruction Feature Selection for Partial Multi-Label Learning Discrimina- tive and correlative partial multi-label learning

Reference 2008

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:42:34.182584Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation fae6087b-8d70-4d14-8101-8da63412cb71 · outbound

This paper cites Simultaneous prediction of multiple chemical parameters of river water quality with tilde.

Noise-Resistant Label Reconstruction Feature Selection for Partial Multi-Label Learning Simultaneous prediction of multiple chemical parameters of river water quality with tilde

Reference 2009

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:42:35.192209Z

Source-reported events for the cited work

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Observation e9eb7cc7-8283-41db-982c-59af444c819b · outbound

This paper cites Graph-based multi-label disease prediction model learning from medi- cal data and domain knowledge.

Noise-Resistant Label Reconstruction Feature Selection for Partial Multi-Label Learning Graph-based multi-label disease prediction model learning from medi- cal data and domain knowledge

Reference 2010

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:42:34.518292Z

Source-reported events for the cited work

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Observation 1adbea64-d0bf-4aea-8b5b-4a9a9263b0d3 · outbound

This paper cites Survey on svm and their application in image classification.

Noise-Resistant Label Reconstruction Feature Selection for Partial Multi-Label Learning Survey on svm and their application in image classification

Reference 2013

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:42:35.102646Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 7100d0e8-4aff-4e87-999a-ddab5af8544a · outbound

This paper cites Semi- supervised multi-label learning by constrained non- negative matrix factorization.

Noise-Resistant Label Reconstruction Feature Selection for Partial Multi-Label Learning Semi- supervised multi-label learning by constrained non- negative matrix factorization

Reference 2015

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:42:34.678285Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation e2620d7a-5f3c-4219-a230-db1eecbf1b15 · outbound

This paper cites Recovering Accurate Labeling Information from Partially Valid Data for Effective Multi-Label Learning.

Noise-Resistant Label Reconstruction Feature Selection for Partial Multi-Label Learning Recovering Accurate Labeling Information from Partially Valid Data for Effective Multi-Label Learning

Reference 2016

Resolution: verified exact; local_arxiv, observed 2026-08-07T10:42:33.454992Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 39d6db9e-af8a-4a11-98ad-af82ad50b2e0 · outbound

This paper cites A mathematical theory of communication.

Noise-Resistant Label Reconstruction Feature Selection for Partial Multi-Label Learning A mathematical theory of communication

Reference 2017

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:42:34.377014Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 3e7e57c6-9473-40b3-8ac5-6440a1e8933a · outbound

This paper cites A unified low-order information-theoretic feature selection framework for multi-label learning.

Noise-Resistant Label Reconstruction Feature Selection for Partial Multi-Label Learning A unified low-order information-theoretic feature selection framework for multi-label learning

Reference 2018

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:42:34.948620Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 8749366e-a576-4a90-859f-ad86909f2ab6 · outbound

This paper cites Object recogni- tion as machine translation: Learning a lexicon for a fixed image vocabulary.

Noise-Resistant Label Reconstruction Feature Selection for Partial Multi-Label Learning Object recogni- tion as machine translation: Learning a lexicon for a fixed image vocabulary

Reference 2019

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:42:35.030876Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation ee75649c-a7c1-4d72-8c28-02f97c276a57 · outbound

This paper cites Partial multi-label feature selection via subspace optimiza- tion.

Noise-Resistant Label Reconstruction Feature Selection for Partial Multi-Label Learning Partial multi-label feature selection via subspace optimiza- tion

Reference 2020

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:42:34.885331Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 6fc350df-327c-4472-b1a5-4fa27c55f1df · outbound

This paper cites Learning a deep convnet for multi-label classification with partial labels.

Noise-Resistant Label Reconstruction Feature Selection for Partial Multi-Label Learning Learning a deep convnet for multi-label classification with partial labels

Reference 2021

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:42:35.056621Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation e7d44139-8784-4805-b078-c55a2980f58c · outbound

This paper cites Scalable multi-label classification.

Noise-Resistant Label Reconstruction Feature Selection for Partial Multi-Label Learning Scalable multi-label classification

Reference 2022

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:42:34.474149Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 72c71a25-7595-4702-855b-158e05c3365e · outbound

This paper cites Distributed multi-label feature selection using individual mutual information mea- sures.

Noise-Resistant Label Reconstruction Feature Selection for Partial Multi-Label Learning Distributed multi-label feature selection using individual mutual information mea- sures

Reference 2023

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:42:34.925456Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 2a6fda77-5dc4-406f-9156-c9250c3daa75 · outbound

This paper cites Multi-label feature selection based on max-dependency and min-redundancy.

Noise-Resistant Label Reconstruction Feature Selection for Partial Multi-Label Learning Multi-label feature selection based on max-dependency and min-redundancy

Reference 2024

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:42:34.719453Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Pith citing papers

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