JP2024540956A - 訓練されたモデルのバイアス評価のための技術 - Google Patents

訓練されたモデルのバイアス評価のための技術 Download PDF

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JP2024540956A
JP2024540956A JP2024523727A JP2024523727A JP2024540956A JP 2024540956 A JP2024540956 A JP 2024540956A JP 2024523727 A JP2024523727 A JP 2024523727A JP 2024523727 A JP2024523727 A JP 2024523727A JP 2024540956 A JP2024540956 A JP 2024540956A
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bias
model
data
trained
synthetic
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JP2024540956A5 (https=
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サンカラナラヤナン，ハリ・バスカー
レザ，シャヒード
カティヤール，アルピット
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オラクル・インターナショナル・コーポレイション
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    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N20/00—Machine learning
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N3/00—Computing arrangements based on biological models
    • G06N3/02—Neural networks
    • G06N3/08—Learning methods
    • G06N3/088—Non-supervised learning, e.g. competitive learning
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N3/00—Computing arrangements based on biological models
    • G06N3/02—Neural networks
    • G06N3/04—Architecture, e.g. interconnection topology
    • G06N3/045—Combinations of networks
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N3/00—Computing arrangements based on biological models
    • G06N3/02—Neural networks
    • G06N3/04—Architecture, e.g. interconnection topology
    • G06N3/0475—Generative networks
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N5/00—Computing arrangements using knowledge-based models
    • G06N5/02—Knowledge representation; Symbolic representation
    • G06N5/022—Knowledge engineering; Knowledge acquisition

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JP2024523727A 2021-10-22 2022-08-17 訓練されたモデルのバイアス評価のための技術 Pending JP2024540956A (ja)

Applications Claiming Priority (3)

Application Number Priority Date Filing Date Title
US17/508,734 US20230131834A1 (en) 2021-10-22 2021-10-22 Techniques for trained model bias assessment
US17/508,734 2021-10-22
PCT/US2022/075052 WO2023069799A1 (en) 2021-10-22 2022-08-16 Techniques for trained model bias assessment

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JP2024540956A true JP2024540956A (ja) 2024-11-06
JP2024540956A5 JP2024540956A5 (https=) 2025-07-23

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JP2024523727A Pending JP2024540956A (ja) 2021-10-22 2022-08-17 訓練されたモデルのバイアス評価のための技術

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US (1) US20230131834A1 (https=)
EP (1) EP4420051A1 (https=)
JP (1) JP2024540956A (https=)
CN (1) CN118140238A (https=)
WO (1) WO2023069799A1 (https=)

Families Citing this family (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US12353473B2 (en) * 2022-07-07 2025-07-08 Hewlett Packard Enterprise Development Lp Image data bias detection with explainability in machine learning
US20240111995A1 (en) * 2022-10-04 2024-04-04 International Business Machines Corporation Predicting future possibility of bias in an artificial intelligence model
US20250148657A1 (en) * 2023-11-02 2025-05-08 Sony Group Corporation Dataset-level societal bias mitigation with text-to-image model

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* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US11625647B2 (en) * 2018-05-25 2023-04-11 Todd Marlin Methods and systems for facilitating analysis of a model
US20220114399A1 (en) * 2020-10-08 2022-04-14 Royal Bank Of Canada System and method for machine learning fairness testing

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WO2023069799A8 (en) 2024-04-18
CN118140238A (zh) 2024-06-04
US20230131834A1 (en) 2023-04-27
EP4420051A1 (en) 2024-08-28
WO2023069799A1 (en) 2023-04-27

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