JP2024540956A5 - - Google Patents
Info
- Publication number
- JP2024540956A5 JP2024540956A5 JP2024523727A JP2024523727A JP2024540956A5 JP 2024540956 A5 JP2024540956 A5 JP 2024540956A5 JP 2024523727 A JP2024523727 A JP 2024523727A JP 2024523727 A JP2024523727 A JP 2024523727A JP 2024540956 A5 JP2024540956 A5 JP 2024540956A5
- Authority
- JP
- Japan
- Prior art keywords
- bias
- model
- trained model
- computing system
- generating
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
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 |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| JP2024540956A JP2024540956A (ja) | 2024-11-06 |
| JP2024540956A5 true JP2024540956A5 (https=) | 2025-07-23 |
Family
ID=83271693
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| 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 |
Country Status (5)
| Country | Link |
|---|---|
| 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)
| 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 |
Family Cites Families (2)
| 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 |
-
2021
- 2021-10-22 US US17/508,734 patent/US20230131834A1/en active Pending
-
2022
- 2022-08-16 WO PCT/US2022/075052 patent/WO2023069799A1/en not_active Ceased
- 2022-08-17 CN CN202280070137.7A patent/CN118140238A/zh active Pending
- 2022-08-17 JP JP2024523727A patent/JP2024540956A/ja active Pending
- 2022-08-17 EP EP22768577.3A patent/EP4420051A1/en active Pending
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| US20210042590A1 (en) | Machine learning system using a stochastic process and method | |
| JP2024540956A5 (https=) | ||
| Molnar et al. | Pitfalls to avoid when interpreting machine learning models | |
| JP6749468B2 (ja) | 評価モデルのためのモデリング方法及び装置 | |
| WO2021027052A1 (zh) | 面向神经网络模型的基于层间剖析的输入实例验证方法 | |
| CN112597302A (zh) | 基于多维评论表示的虚假评论检测方法 | |
| CN112668809B (zh) | 建立自闭症儿童康复效果预测模型的方法 | |
| JP7554528B1 (ja) | 情報処理装置、推論装置、機械学習装置、情報処理方法、推論方法、及び、機械学習方法 | |
| US12147884B2 (en) | Feature pruning and algorithm selection for machine learning | |
| CN117608648A (zh) | 一种零样本大模型生成代码检测方法和系统 | |
| FI4036816T3 (fi) | Virheiden lieventäminen kvanttitietoprosessoreja käyttäen suoritettavissa algoritmeissa | |
| CN115114421A (zh) | 一种问答模型训练方法 | |
| CN117237479A (zh) | 基于扩散模型的产品风格自动生成方法、装置及设备 | |
| CN118196567A (zh) | 基于大语言模型的数据评价方法、装置、设备及存储介质 | |
| CN118861960A (zh) | 基于电力大数据的用电异常识别方法、装置、设备及介质 | |
| AU2021312671B2 (en) | Value over replacement feature (VORF) based determination of feature importance in machine learning | |
| Papadopoulos et al. | Reliable Confidence Intervals for Software Effort Estimation. | |
| CN107784411A (zh) | 模型中关键变量的探测方法及装置 | |
| KR20230049486A (ko) | 정치성향 분석 장치 및 이를 이용한 서비스 제공 방법 | |
| CN120067327A (zh) | 基于图卷积神经网络的技术成熟度计算系统和方法 | |
| CN119088700A (zh) | 一种基于动态特征选择与超采样的汽车软件缺陷预测方法 | |
| CN116049733B (zh) | 基于神经网络的效能评估方法、系统、设备与存储介质 | |
| CN110580261A (zh) | 针对高科技公司的深度技术追踪方法 | |
| CN113656279B (zh) | 基于残差网络和度量注意机制的代码气味检测方法 | |
| CN112288032B (zh) | 一种基于生成对抗网络的量化模型训练的方法及装置 |