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Paper Citation Record · LEDGER

MARLINE: Multi-Source Mapping Transfer Learning for Non-Stationary Environments

As of 5 August 2026, this Paper Citation Record lists 32 of 32 outbound references and 0 inbound Pith citation observations for arXiv:2509.08176.

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

pith.paper-citation-record.v1
2509.08176 v1

Coverage vector

measured 32 of 32 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-04T21:12:39.657537Z

measured 32 of 32 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-04T06:34:03.388597+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

32 of 32 outbound references displayed

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  • unresolved3
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 7b8b4038-01f3-4851-9f31-8b2dc9c940df · outbound

This paper cites Learning under concept drift: A review,.

MARLINE: Multi-Source Mapping Transfer Learning for Non-Stationary Environments Learning under concept drift: A review,

Reference 1

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Observation a4e7bf03-45a6-4098-8542-6e731f44e232 · outbound

This paper cites Multi-source transfer learning for non-stationary environments,.

MARLINE: Multi-Source Mapping Transfer Learning for Non-Stationary Environments Multi-source transfer learning for non-stationary environments,

Reference 2

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Source-reported events for the cited work

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Observation 6b95c9b2-412f-4237-b3df-237a9a0ee5a7 · outbound

This paper cites Online non-stationary boosting.

MARLINE: Multi-Source Mapping Transfer Learning for Non-Stationary Environments Online non-stationary boosting

Reference 3

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Observation e19205fb-c299-4ede-9d49-b65b0de984bc · outbound

This paper cites Learning in nonsta- tionary environments: A survey,.

MARLINE: Multi-Source Mapping Transfer Learning for Non-Stationary Environments Learning in nonsta- tionary environments: A survey,

Reference 4

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Observation 2885f2a4-a148-448f-bb16-2e9eca2778f2 · outbound

This paper cites Transfer learning in non-stationary environments,.

MARLINE: Multi-Source Mapping Transfer Learning for Non-Stationary Environments Transfer learning in non-stationary environments,

Reference 5

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Observation de947a23-a90f-4ae5-aa40-9083f28ea147 · outbound

This paper cites A survey on concept drift adaptation,.

MARLINE: Multi-Source Mapping Transfer Learning for Non-Stationary Environments A survey on concept drift adaptation,

Reference 6

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Observation d5ad2cdb-897e-45ed-a621-aa94381bfa41 · outbound

This paper cites A survey on transfer learning,.

MARLINE: Multi-Source Mapping Transfer Learning for Non-Stationary Environments A survey on transfer learning,

Reference 7

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Source-reported events for the cited work

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Observation fa1f966d-7d83-457f-934e-c3f38e6a3bbc · outbound

This paper cites Multistream classification with relative density ratio estimation,.

MARLINE: Multi-Source Mapping Transfer Learning for Non-Stationary Environments Multistream classification with relative density ratio estimation,

Reference 8

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Source-reported events for the cited work

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Observation 56ffbeb9-2bb3-4ca7-8a24-9792b96e26db · outbound

This paper cites Comc: A framework for online cross-domain multistream classification,.

MARLINE: Multi-Source Mapping Transfer Learning for Non-Stationary Environments Comc: A framework for online cross-domain multistream classification,

Reference 9

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Source-reported events for the cited work

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Observation 3fddd554-157c-402b-8856-068b77a87e5c · outbound

This paper cites London bike sharing dataset, https://www.kaggle.com/hmavrodiev/ london-bike-sharing-dataset,.

MARLINE: Multi-Source Mapping Transfer Learning for Non-Stationary Environments London bike sharing dataset, https://www.kaggle.com/hmavrodiev/ london-bike-sharing-dataset,

Reference 10

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Source-reported events for the cited work

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Observation d9d3f2a5-f838-410a-9c30-6b6b796b1569 · outbound

This paper cites Event labeling combining ensemble detectors and background knowledge,.

MARLINE: Multi-Source Mapping Transfer Learning for Non-Stationary Environments Event labeling combining ensemble detectors and background knowledge,

Reference 11

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Source-reported events for the cited work

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Observation 7e86af13-39d4-41da-968d-b6dec17d6c50 · outbound

This paper cites How to make best use of cross-company data in software effort estimation?.

MARLINE: Multi-Source Mapping Transfer Learning for Non-Stationary Environments How to make best use of cross-company data in software effort estimation?

Reference 12

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

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Observation 33ad0358-f559-4ba2-8561-8472a33d350b · outbound

This paper cites Ensemble learning for data stream analysis: A survey,.

MARLINE: Multi-Source Mapping Transfer Learning for Non-Stationary Environments Ensemble learning for data stream analysis: A survey,

Reference 13

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Source-reported events for the cited work

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Observation 6f3f7fce-05d4-4e49-a03e-ffd249a71dce · outbound

This paper cites Adaptive random forests for evolving data stream classification,.

MARLINE: Multi-Source Mapping Transfer Learning for Non-Stationary Environments Adaptive random forests for evolving data stream classification,

Reference 14

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Source-reported events for the cited work

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Observation 63843c3d-0d44-46ad-8914-a70752b226fe · outbound

This paper cites Learning with drift detection,.

MARLINE: Multi-Source Mapping Transfer Learning for Non-Stationary Environments Learning with drift detection,

Reference 15

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Source-reported events for the cited work

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Observation 5703c098-8e11-47c3-9a59-fbf49ebeaed4 · outbound

This paper cites Online and non- parametric drift detection methods based on hoeffding’s bounds,.

MARLINE: Multi-Source Mapping Transfer Learning for Non-Stationary Environments Online and non- parametric drift detection methods based on hoeffding’s bounds,

Reference 16

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Source-reported events for the cited work

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Observation f5855259-ee69-4191-9ff1-82bb533bf6cd · outbound

This paper cites Dynamic weighted majority: An ensemble method for drifting concepts,.

MARLINE: Multi-Source Mapping Transfer Learning for Non-Stationary Environments Dynamic weighted majority: An ensemble method for drifting concepts,

Reference 17

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Observation 63ef2296-56b0-48f1-9f63-b4bbb389e6bc · outbound

This paper cites DDD: a new ensemble approach for dealing with concept drift,.

MARLINE: Multi-Source Mapping Transfer Learning for Non-Stationary Environments DDD: a new ensemble approach for dealing with concept drift,

Reference 18

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Observation e9ae8dd4-c87f-4a5d-980e-000c58fd0b50 · outbound

This paper cites Online transfer learning,.

MARLINE: Multi-Source Mapping Transfer Learning for Non-Stationary Environments Online transfer learning,

Reference 19

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Source-reported events for the cited work

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Observation 42e0f627-4b31-4279-96cb-235028bcce5c · outbound

This paper cites Concept drift adaptation by exploiting historical knowledge,.

MARLINE: Multi-Source Mapping Transfer Learning for Non-Stationary Environments Concept drift adaptation by exploiting historical knowledge,

Reference 20

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Observation 5800ff8d-952a-4f71-8753-907c27ebafd5 · outbound

This paper cites Code repository for MARLINE: Multi-source mapping transfer- learning for non-stationary environments,.

MARLINE: Multi-Source Mapping Transfer Learning for Non-Stationary Environments Code repository for MARLINE: Multi-source mapping transfer- learning for non-stationary environments,

Reference 21

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Source-reported events for the cited work

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This paper cites Online bagging and boosting,.

MARLINE: Multi-Source Mapping Transfer Learning for Non-Stationary Environments Online bagging and boosting,

Reference 22

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

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Observation 7d2cec40-f00c-4451-8fa3-a3cfbc4c4909 · outbound

This paper cites Supplementary material for MARLINE: Multi-source mapping transferlearning for non-stationary environments,.

MARLINE: Multi-Source Mapping Transfer Learning for Non-Stationary Environments Supplementary material for MARLINE: Multi-source mapping transferlearning for non-stationary environments,

Reference 23

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Observation 9d0ec7cb-8096-4cf9-976c-fedc49a4dd54 · outbound

This paper cites Moa: Massive online analysis,.

MARLINE: Multi-Source Mapping Transfer Learning for Non-Stationary Environments Moa: Massive online analysis,

Reference 24

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This paper cites Mining high-speed data streams,.

MARLINE: Multi-Source Mapping Transfer Learning for Non-Stationary Environments Mining high-speed data streams,

Reference 25

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No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

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Observation 73f8c443-b2cb-4056-b6d5-19582a71fc2b · outbound

This paper cites An overview and comprehensive comparison of ensembles for concept drift,.

MARLINE: Multi-Source Mapping Transfer Learning for Non-Stationary Environments An overview and comprehensive comparison of ensembles for concept drift,

Reference 26

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No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

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This paper cites Issues in evaluation of stream learning algorithms,.

MARLINE: Multi-Source Mapping Transfer Learning for Non-Stationary Environments Issues in evaluation of stream learning algorithms,

Reference 27

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Source-reported events for the cited work

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Observation 35f0b327-a13e-45e1-bbc8-7c9fc516b50f · outbound

This paper cites an unresolved cited work.

MARLINE: Multi-Source Mapping Transfer Learning for Non-Stationary Environments Unresolved cited work

Reference 28

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Source-reported events for the cited work

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Observation 6ad217b9-b482-475e-954e-5b08005190b5 · outbound

This paper cites Significance test for sphericity of a normal n-variate distribution,.

MARLINE: Multi-Source Mapping Transfer Learning for Non-Stationary Environments Significance test for sphericity of a normal n-variate distribution,

Reference 29

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

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Observation 6e624fc1-9fc1-44d8-a10a-d77dbe33c52b · outbound

This paper cites On methods in the analysis of profile data,.

MARLINE: Multi-Source Mapping Transfer Learning for Non-Stationary Environments On methods in the analysis of profile data,

Reference 30

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Source-reported events for the cited work

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Observation c9662d8a-1530-4c68-8ada-256831323ba3 · outbound

This paper cites Estimation of the box correction for degrees of freedom from sample data in randomized block and split- plot designs,.

MARLINE: Multi-Source Mapping Transfer Learning for Non-Stationary Environments Estimation of the box correction for degrees of freedom from sample data in randomized block and split- plot designs,

Reference 31

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Source-reported events for the cited work

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Observation 2889e63d-98bd-455d-995d-b423ca3ef6b9 · outbound

This paper cites Verma,Repeated measures design for empirical researchers.

MARLINE: Multi-Source Mapping Transfer Learning for Non-Stationary Environments Verma,Repeated measures design for empirical researchers

Reference 32

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

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Pith citing papers

No inbound Pith citation observations are available.