Efficient Data Valuation Approximation in Federated Learning: A Sampling-based Approach | Paper Citation Record

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This paper cites Advances and open problems in federated learning,.

Efficient Data Valuation Approximation in Federated Learning: A Sampling-based Approach Advances and open problems in federated learning,

Reference 1

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This paper cites Federated machine learning: Concept and applications,.

Efficient Data Valuation Approximation in Federated Learning: A Sampling-based Approach Federated machine learning: Concept and applications,

Reference 2

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This paper cites Heterogeneous federated learning: State- of-the-art and research challenges,.

Efficient Data Valuation Approximation in Federated Learning: A Sampling-based Approach Heterogeneous federated learning: State- of-the-art and research challenges,

Reference 3

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This paper cites A survey on federated learning systems: Vision, hype and reality for data privacy and protection,.

Efficient Data Valuation Approximation in Federated Learning: A Sampling-based Approach A survey on federated learning systems: Vision, hype and reality for data privacy and protection,

Reference 4

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

Efficient Data Valuation Approximation in Federated Learning: A Sampling-based Approach Communication-efficient learning of deep networks from decentralized data,

Reference 5

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Observation ebba24ab-b3f6-4a09-bffd-ea54f5ebff8a · outbound

This paper cites Profit allocation for federated learning,.

Efficient Data Valuation Approximation in Federated Learning: A Sampling-based Approach Profit allocation for federated learning,

Reference 6

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Observation dac89fe9-ffe3-412c-9061-374cfbfd90b2 · outbound

This paper cites Efficient participant contribu- tion evaluation for horizontal and vertical federated learning,.

Efficient Data Valuation Approximation in Federated Learning: A Sampling-based Approach Efficient participant contribu- tion evaluation for horizontal and vertical federated learning,

Reference 7

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Observation 58f0923a-3d4a-4b7c-ba40-30ec3793f328 · outbound

This paper cites Equitable data valuation meets the right to be forgotten in model markets,.

Efficient Data Valuation Approximation in Federated Learning: A Sampling-based Approach Equitable data valuation meets the right to be forgotten in model markets,

Reference 8

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Observation 98c35335-55a8-4376-9354-c776de3b4a29 · outbound

This paper cites Efficient and fair data valuation for horizontal federated learning,.

Efficient Data Valuation Approximation in Federated Learning: A Sampling-based Approach Efficient and fair data valuation for horizontal federated learning,

Reference 9

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Observation 01f9b702-3647-4f34-a1e5-6db1ccc2592d · outbound

This paper cites A principled approach to data valuation for federated learning,.

Efficient Data Valuation Approximation in Federated Learning: A Sampling-based Approach A principled approach to data valuation for federated learning,

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:06:04.760297Z

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Observation 45337593-8f7c-421f-80e1-109d6823f5ab · outbound

This paper cites Efficient task-specific data valuation for nearest neighbor algorithms,.

Efficient Data Valuation Approximation in Federated Learning: A Sampling-based Approach Efficient task-specific data valuation for nearest neighbor algorithms,

Reference 11

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Observation 2b667add-654e-42f3-ad93-4580e5333fdc · outbound

This paper cites Gtg-shapley: Efficient and accurate participant contribution evaluation in federated learning,.

Efficient Data Valuation Approximation in Federated Learning: A Sampling-based Approach Gtg-shapley: Efficient and accurate participant contribution evaluation in federated learning,

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:06:04.736477Z

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Observation 67e3566e-d614-40c6-8aa4-64530efcbc4c · outbound

This paper cites Contributions estimation in federated learning: A comprehensive experimental evaluation,.

Efficient Data Valuation Approximation in Federated Learning: A Sampling-based Approach Contributions estimation in federated learning: A comprehensive experimental evaluation,

Reference 13

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This paper cites Myerson, Game theory.

Efficient Data Valuation Approximation in Federated Learning: A Sampling-based Approach Myerson, Game theory

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:06:04.713339Z

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Observation b5df7dac-b536-4657-812e-2b72a949a2fc · outbound

This paper cites The shapley value in database management,.

Efficient Data Valuation Approximation in Federated Learning: A Sampling-based Approach The shapley value in database management,

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:06:04.701864Z

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Observation c32f266a-1e0c-4508-bec4-c4603d95c573 · outbound

This paper cites The shapley value in machine learning,.

Efficient Data Valuation Approximation in Federated Learning: A Sampling-based Approach The shapley value in machine learning,

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:06:04.691117Z

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Observation bdbcd79b-554b-4c67-ad31-1388258a4424 · outbound

This paper cites Data shapley: Equitable valuation of data for machine learning,.

Efficient Data Valuation Approximation in Federated Learning: A Sampling-based Approach Data shapley: Equitable valuation of data for machine learning,

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:06:04.680578Z

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Observation 7d048abf-54ed-4b9f-ad4f-b0b4e3cc3b16 · outbound

This paper cites Towards efficient data valuation based on the shapley value,.

Efficient Data Valuation Approximation in Federated Learning: A Sampling-based Approach Towards efficient data valuation based on the shapley value,

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:06:04.669554Z

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Observation 4e35a0d4-19d3-49e5-9e4c-91281ec7eb51 · outbound

This paper cites Efficient sampling approaches to shapley value approximation,.

Efficient Data Valuation Approximation in Federated Learning: A Sampling-based Approach Efficient sampling approaches to shapley value approximation,

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:06:04.657646Z

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This paper cites On the complexity of cooperative solution concepts,.

Efficient Data Valuation Approximation in Federated Learning: A Sampling-based Approach On the complexity of cooperative solution concepts,

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:06:04.645305Z

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Observation fa12abb1-231a-45ae-9487-0bd13affdf3d · outbound

This paper cites Data banzhaf: A robust data valuation framework for machine learning,.

Efficient Data Valuation Approximation in Federated Learning: A Sampling-based Approach Data banzhaf: A robust data valuation framework for machine learning,

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:06:04.633161Z

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Observation 33544d70-e41e-4edd-9f1e-f718c6d192d5 · outbound

This paper cites The truth about linear regression,.

Efficient Data Valuation Approximation in Federated Learning: A Sampling-based Approach The truth about linear regression,

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:06:04.621426Z

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Observation 26e25bee-bd37-47b2-9f82-7010b8e57e77 · outbound

This paper cites LEAF: A Benchmark for Federated Settings.

Efficient Data Valuation Approximation in Federated Learning: A Sampling-based Approach LEAF: A Benchmark for Federated Settings

Reference 23

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This paper cites Model-sharing games: Analyzing federated learning under voluntary participation,.

Efficient Data Valuation Approximation in Federated Learning: A Sampling-based Approach Model-sharing games: Analyzing federated learning under voluntary participation,

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:06:04.609857Z

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This paper cites The MNIST Database,.

Efficient Data Valuation Approximation in Federated Learning: A Sampling-based Approach The MNIST Database,

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:06:04.598678Z

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This paper cites Barry and R.

Efficient Data Valuation Approximation in Federated Learning: A Sampling-based Approach Barry and R

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:06:04.587987Z

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This paper cites Tensorflow federated,.

Efficient Data Valuation Approximation in Federated Learning: A Sampling-based Approach Tensorflow federated,

Reference 27

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Observation 98a93c71-1b13-40e8-9f0f-0bb9c67b961c · outbound

This paper cites Vf 2boost: Very fast vertical federated gradient boosting for cross-enterprise learning,.

Efficient Data Valuation Approximation in Federated Learning: A Sampling-based Approach Vf 2boost: Very fast vertical federated gradient boosting for cross-enterprise learning,

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:06:04.565919Z

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Observation 491261e5-08b3-4143-81d2-f6d953b67061 · outbound

This paper cites Blindfl: Vertical federated machine learning without peeking into your data,.

Efficient Data Valuation Approximation in Federated Learning: A Sampling-based Approach Blindfl: Vertical federated machine learning without peeking into your data,

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:06:04.553572Z

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This paper cites Tensorflow: A system for large-scale machine learning,.

Efficient Data Valuation Approximation in Federated Learning: A Sampling-based Approach Tensorflow: A system for large-scale machine learning,

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:06:04.541226Z

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Observation 088381a8-8123-47f4-aa99-2f6e1253d134 · outbound

This paper cites The general data protection regulation (GDPR),.

Efficient Data Valuation Approximation in Federated Learning: A Sampling-based Approach The general data protection regulation (GDPR),

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:06:04.527209Z

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This paper cites A guide to the california consumer privacy act of 2018,.

Efficient Data Valuation Approximation in Federated Learning: A Sampling-based Approach A guide to the california consumer privacy act of 2018,

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:06:04.515453Z

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Observation 25ebd325-8fa5-4c5f-a1cd-2ea8f6655756 · outbound

This paper cites Federated optimization in heterogeneous networks,.

Efficient Data Valuation Approximation in Federated Learning: A Sampling-based Approach Federated optimization in heterogeneous networks,

Reference 33

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This paper cites SCAFFOLD: stochastic controlled averaging for federated learning,.

Efficient Data Valuation Approximation in Federated Learning: A Sampling-based Approach SCAFFOLD: stochastic controlled averaging for federated learning,

Reference 34

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Observation f2d2a8d1-7295-4338-b394-22859c7e65f5 · outbound

This paper cites Fs-real: A real-world cross-device federated learning platform,.

Efficient Data Valuation Approximation in Federated Learning: A Sampling-based Approach Fs-real: A real-world cross-device federated learning platform,

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:06:04.481309Z

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No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

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This paper cites Fs-real: Towards real-world cross-device federated learning,.

Efficient Data Valuation Approximation in Federated Learning: A Sampling-based Approach Fs-real: Towards real-world cross-device federated learning,

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:06:04.467743Z

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This paper cites Fedmp: Federated learning through adaptive model pruning in heterogeneous edge computing,.

Efficient Data Valuation Approximation in Federated Learning: A Sampling-based Approach Fedmp: Federated learning through adaptive model pruning in heterogeneous edge computing,

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:06:04.454805Z

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Observation 640dc980-c82e-4901-b923-83df29db4496 · outbound

This paper cites Enhancing decentralized federated learning for non-iid data on heterogeneous devices,.

Efficient Data Valuation Approximation in Federated Learning: A Sampling-based Approach Enhancing decentralized federated learning for non-iid data on heterogeneous devices,

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:06:04.442759Z

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Observation c870689a-8a38-4286-97f2-001588a126a4 · outbound

This paper cites No one left behind: Inclusive federated learning over heterogeneous devices,.

Efficient Data Valuation Approximation in Federated Learning: A Sampling-based Approach No one left behind: Inclusive federated learning over heterogeneous devices,

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:06:04.429865Z

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Observation 3285feb3-ae05-4fdf-9eb5-a50855052b46 · outbound

This paper cites Personalized cross-silo federated learning on non-iid data,.

Efficient Data Valuation Approximation in Federated Learning: A Sampling-based Approach Personalized cross-silo federated learning on non-iid data,

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:06:04.416800Z

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Observation 289d6f7a-5af1-4091-89e1-650f89a67ef9 · outbound

This paper cites Federated learning on non-iid data silos: An experimental study,.

Efficient Data Valuation Approximation in Federated Learning: A Sampling-based Approach Federated learning on non-iid data silos: An experimental study,

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:06:04.405273Z

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Observation 8375f3d4-41aa-4880-ad86-21cc3260bec7 · outbound

This paper cites Privacy preserving vertical federated learning for tree-based models,.

Efficient Data Valuation Approximation in Federated Learning: A Sampling-based Approach Privacy preserving vertical federated learning for tree-based models,

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:06:04.393757Z

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Observation ced1d1e2-4d67-4ca1-b1fe-da4006f7e65b · outbound

This paper cites Practical federated gradient boosting decision trees,.

Efficient Data Valuation Approximation in Federated Learning: A Sampling-based Approach Practical federated gradient boosting decision trees,

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:06:04.381109Z

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Observation cd190938-4f9d-417f-b483-dfec68038e62 · outbound

This paper cites A value forn-person games,.

Efficient Data Valuation Approximation in Federated Learning: A Sampling-based Approach A value forn-person games,

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:06:04.368320Z

Source-reported events for the cited work

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Observation e700ef48-6175-403d-933c-c191d4b50a6e · outbound

This paper cites Secure shapley value for cross- silo federated learning,.

Efficient Data Valuation Approximation in Federated Learning: A Sampling-based Approach Secure shapley value for cross- silo federated learning,

Reference 45

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:06:04.356104Z

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Observation 750284ae-886b-41a6-a671-70d3543cede7 · outbound

This paper cites Gradient driven rewards to guarantee fairness in collaborative machine learning,.

Efficient Data Valuation Approximation in Federated Learning: A Sampling-based Approach Gradient driven rewards to guarantee fairness in collaborative machine learning,

Reference 46

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:06:04.342662Z

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Observation 0e03f45a-96c4-42d7-a128-3c699ad87199 · outbound

This paper cites Validation free and replication robust volume-based data valuation,.

Efficient Data Valuation Approximation in Federated Learning: A Sampling-based Approach Validation free and replication robust volume-based data valuation,

Reference 47

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:06:04.330147Z

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Observation c04442e0-03ea-494c-b1f9-1efc7e95b3e1 · outbound

This paper cites Fast, robust and interpretable participant contribution estimation for federated learning,.

Efficient Data Valuation Approximation in Federated Learning: A Sampling-based Approach Fast, robust and interpretable participant contribution estimation for federated learning,

Reference 48

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:06:04.316337Z

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