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Paper Citation Record · LEDGER

Improving the Accuracy of Principal Component Analysis by the Maximum Entropy Method

As of 8 August 2026, this Paper Citation Record lists 14 of 14 outbound references and 0 inbound Pith citation observations for arXiv:1907.11094.

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

pith.paper-citation-record.v1
1907.11094 v1

Coverage vector

measured 14 of 14 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-05-24T17:05:55.178660Z

measured 14 of 14 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+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

14 of 14 outbound references displayed

  • verified exact0
  • verified fuzzy11
  • unresolved3
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation b99bad0f-f73a-4fc9-8145-ceed2fda73d2 · outbound

This paper cites A haplotype map of the human genome.

Improving the Accuracy of Principal Component Analysis by the Maximum Entropy Method A haplotype map of the human genome

Reference 1

Resolution
verified fuzzy
raw_fallback, observed 2026-05-24T17:06:17.127475Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-05-24T17:05:55.178660Z digest=sha256:28678cec06ddef187f1f3d691c6cdcfa863ffe244973cbd2516cb6cf377bd20c

Observation eb180495-f9da-4759-b162-0b6b0f19df88 · outbound

This paper cites Burges, Dimension Reduction: A Guided Tour.

Improving the Accuracy of Principal Component Analysis by the Maximum Entropy Method Burges, Dimension Reduction: A Guided Tour

Reference 2

Resolution
verified fuzzy
raw_fallback, observed 2026-05-24T17:06:17.138604Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-05-24T17:05:55.178660Z digest=sha256:7b842876100a57857c6b13aa638bfedbe958db33a33827ae24a4bfff7e425e9f

Observation 2a6acbff-0b82-447a-b6e8-2ba9afdce4bf · outbound

This paper cites Gray, Principal Component Analysis: Methods, Applications and Technology, ser.

Improving the Accuracy of Principal Component Analysis by the Maximum Entropy Method Gray, Principal Component Analysis: Methods, Applications and Technology, ser

Reference 3

Resolution
verified fuzzy
raw_fallback, observed 2026-05-24T17:06:17.094743Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-05-24T17:05:55.178660Z digest=sha256:87668379f15db1df56ed735da6521dea728bebb99c4f669f4bdff192837c817c

Observation 291339fd-c6cc-42a9-a6a8-2895a46858df · outbound

This paper cites an unresolved cited work.

Improving the Accuracy of Principal Component Analysis by the Maximum Entropy Method Unresolved cited work

Reference 4

Resolution
unresolved
raw_fallback, observed 2026-05-24T17:06:17.130752Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-05-24T17:05:55.178660Z digest=sha256:9d10e4a9cfb3fc82009278fac2effb1e0ca9c6a03c0308f18c03fa4f4ce0d6b5

Observation 3eedb68d-63b4-42d2-a414-654370126a68 · outbound

This paper cites Heuristic search algorithm for dimensionality reduction optimally com- bining feature selection and feature extraction.

Improving the Accuracy of Principal Component Analysis by the Maximum Entropy Method Heuristic search algorithm for dimensionality reduction optimally com- bining feature selection and feature extraction

Reference 5

Resolution
verified fuzzy
raw_fallback, observed 2026-05-24T17:06:17.123837Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-05-24T17:05:55.178660Z digest=sha256:db67ef79fb4c333d9ce1c6d3253dc0950018694af980fd1c910266bd2a7773ca

Observation 92dbe2fb-4c81-467f-8ec8-e65e278ff4ef · outbound

This paper cites Computing ro bust principal components by A* search.

Improving the Accuracy of Principal Component Analysis by the Maximum Entropy Method Computing ro bust principal components by A* search

Reference 6

Resolution
verified fuzzy
raw_fallback, observed 2026-05-24T17:06:17.101694Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-05-24T17:05:55.178660Z digest=sha256:cc09a6638ad74d771f3f6529421fe8584d8909e9139c43f6bc3b54c4a59990ee

Observation feaf6df6-93ba-4ce8-b68c-0cb7fd5669ba · outbound

This paper cites On relationships between unc entred and column-centred principal component analysis.

Improving the Accuracy of Principal Component Analysis by the Maximum Entropy Method On relationships between unc entred and column-centred principal component analysis

Reference 7

Resolution
verified fuzzy
raw_fallback, observed 2026-05-24T17:06:17.098025Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-05-24T17:05:55.178660Z digest=sha256:cd0343e045b2a3275936cd3f743f74f8ea0383dcae8e6a1ce32b323d5b2fb274

Observation 3c6eb5dc-89af-423b-8d96-c31dd92b3adb · outbound

This paper cites A quantitative analy sis and performance study for similarity-search methods in high-d imensional spaces.

Improving the Accuracy of Principal Component Analysis by the Maximum Entropy Method A quantitative analy sis and performance study for similarity-search methods in high-d imensional spaces

Reference 8

Resolution
verified fuzzy
raw_fallback, observed 2026-05-24T17:06:17.109909Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-05-24T17:05:55.178660Z digest=sha256:057cdb27621a502bc8d66ce4d9dc96a7b58daf75e19f3cd79efcf694633a4ae8

Observation 9a9490e6-07a8-439d-ac98-a26a48e0a7d0 · outbound

This paper cites an unresolved cited work.

Improving the Accuracy of Principal Component Analysis by the Maximum Entropy Method Unresolved cited work

Reference 9

Resolution
unresolved
raw_fallback, observed 2026-05-24T17:06:17.106036Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-05-24T17:05:55.178660Z digest=sha256:2cfb916060ca10870816e16f782ed0b7979e51edfe4aee207e221c41a07166e7

Observation 1527bb7f-9c67-48d1-849e-4696cdace47f · outbound

This paper cites On the rationale of maximum entropy metho ds.

Improving the Accuracy of Principal Component Analysis by the Maximum Entropy Method On the rationale of maximum entropy metho ds

Reference 10

Resolution
verified fuzzy
raw_fallback, observed 2026-05-24T17:06:17.114209Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-05-24T17:05:55.178660Z digest=sha256:24e02cb1a5682cdfe9c32f2ba15854e20345e83a83b591e0d433a79c337e56af

Observation 13171a2a-3540-4364-9d96-ffee081cf0b0 · outbound

This paper cites Papoulis, Probability, random V ariables, and Stochastic Processes , 2nd ed.

Improving the Accuracy of Principal Component Analysis by the Maximum Entropy Method Papoulis, Probability, random V ariables, and Stochastic Processes , 2nd ed

Reference 11

Resolution
verified fuzzy
raw_fallback, observed 2026-05-24T17:06:17.090252Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-05-24T17:05:55.178660Z digest=sha256:2e34fc4ed30d4b218e695b5260a76ec7cafe5f6879a92250143d6be45b847423

Observation 8219f04f-8428-4ef1-9988-a5b083e1570e · outbound

This paper cites Principle of maximum entrop y — Wikipedia, the free encyclopedia.

Improving the Accuracy of Principal Component Analysis by the Maximum Entropy Method Principle of maximum entrop y — Wikipedia, the free encyclopedia

Reference 12

Resolution
verified fuzzy
raw_fallback, observed 2026-05-24T17:06:17.118214Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-05-24T17:05:55.178660Z digest=sha256:a814c3c6526a39e47dcfe66ecb08fe6dd38e0b7b4b7dbfdaef2b280d9bdffc44

Observation d72ee9fa-3f15-461a-bff5-2c966d7a25f7 · outbound

This paper cites More subtle v ersions of the Hadamard inequality.

Improving the Accuracy of Principal Component Analysis by the Maximum Entropy Method More subtle v ersions of the Hadamard inequality

Reference 13

Resolution
verified fuzzy
raw_fallback, observed 2026-05-24T17:06:17.134482Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-05-24T17:05:55.178660Z digest=sha256:44aa4ea67b52f2f7e47fc8f8cd398d941ec92f71a6f95499d19c2d96a2836a86

Observation f6f9fb8a-995e-4666-8803-9619b0a7c79e · outbound

This paper cites an unresolved cited work.

Improving the Accuracy of Principal Component Analysis by the Maximum Entropy Method Unresolved cited work

Reference 14

Resolution
unresolved
raw_fallback, observed 2026-05-24T17:06:17.093071Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-05-24T17:05:55.178660Z digest=sha256:66b3c2a8d5f1d8d085e5f72c4a427a01eef67e2928a87f22e43ebad12df53366

Pith citing papers

No inbound Pith citation observations are available.