WO2019067960A1 - Développement agressif à l'aide de générateurs coopératifs - Google Patents

Développement agressif à l'aide de générateurs coopératifs Download PDF

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Publication number
WO2019067960A1
WO2019067960A1 PCT/US2018/053519 US2018053519W WO2019067960A1 WO 2019067960 A1 WO2019067960 A1 WO 2019067960A1 US 2018053519 W US2018053519 W US 2018053519W WO 2019067960 A1 WO2019067960 A1 WO 2019067960A1
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computer system
data
machine learning
classifier
neural network
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PCT/US2018/053519
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English (en)
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James K. Baker
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D5Ai Llc
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Priority claimed from PCT/US2018/051069 external-priority patent/WO2019067236A1/fr
Application filed by D5Ai Llc filed Critical D5Ai Llc
Priority to EP18862297.1A priority Critical patent/EP3688678A4/fr
Priority to US16/645,710 priority patent/US20200285939A1/en
Priority to CN201880076808.4A priority patent/CN111542843A/zh
Publication of WO2019067960A1 publication Critical patent/WO2019067960A1/fr
Priority to US16/901,608 priority patent/US11410050B2/en
Priority to US17/810,778 priority patent/US11531900B2/en
Priority to US17/815,851 priority patent/US11687788B2/en
Priority to US18/196,855 priority patent/US20230289611A1/en

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    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR 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
    • G06N3/084—Backpropagation, e.g. using gradient descent
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR 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; CALCULATING OR 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
    • G06N3/047—Probabilistic or stochastic networks
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR 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
    • G06N3/048—Activation functions
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR 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
    • G06N3/082—Learning methods modifying the architecture, e.g. adding, deleting or silencing nodes or connections

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  • Engineering & Computer Science (AREA)
  • Physics & Mathematics (AREA)
  • Theoretical Computer Science (AREA)
  • General Health & Medical Sciences (AREA)
  • Computing Systems (AREA)
  • Biomedical Technology (AREA)
  • Biophysics (AREA)
  • Computational Linguistics (AREA)
  • Data Mining & Analysis (AREA)
  • Evolutionary Computation (AREA)
  • Life Sciences & Earth Sciences (AREA)
  • Molecular Biology (AREA)
  • Artificial Intelligence (AREA)
  • General Engineering & Computer Science (AREA)
  • General Physics & Mathematics (AREA)
  • Mathematical Physics (AREA)
  • Software Systems (AREA)
  • Health & Medical Sciences (AREA)
  • Probability & Statistics with Applications (AREA)
  • Hardware Redundancy (AREA)

Abstract

L'invention concerne divers systèmes et procédés permettant d'améliorer le développement agressif de systèmes d'apprentissage machine. Au cours de l'apprentissage machine, un compromis doit être trouvé entre permettre à un système d'apprentissage machine d'apprendre autant qu'il peut des données d'entraînement et obtenir un surapprentissage sur les données d'entraînement. Ce compromis est important car le surapprentissage provoque habituellement la diminution des performances sur les nouvelles données. Toutefois, divers systèmes et procédés peuvent être utilisés pour séparer le processus d'apprentissage détaillé et d'acquisition des connaissances et le processus d'imposition de restrictions et de lissage des estimations, ce qui permet à des systèmes d'apprentissage machine d'apprendre de manière agressive des données d'entraînement, tout en atténuant les effets de surapprentissage sur les données d'entraînement.
PCT/US2018/053519 2017-09-28 2018-09-28 Développement agressif à l'aide de générateurs coopératifs WO2019067960A1 (fr)

Priority Applications (7)

Application Number Priority Date Filing Date Title
EP18862297.1A EP3688678A4 (fr) 2017-09-28 2018-09-28 Développement agressif à l'aide de générateurs coopératifs
US16/645,710 US20200285939A1 (en) 2017-09-28 2018-09-28 Aggressive development with cooperative generators
CN201880076808.4A CN111542843A (zh) 2017-09-28 2018-09-28 利用协作生成器积极开发
US16/901,608 US11410050B2 (en) 2017-09-28 2020-06-15 Imitation training for machine learning systems with synthetic data generators
US17/810,778 US11531900B2 (en) 2017-09-28 2022-07-05 Imitation learning for machine learning systems with synthetic data generators
US17/815,851 US11687788B2 (en) 2017-09-28 2022-07-28 Generating synthetic data examples as interpolation of two data examples that is linear in the space of relative scores
US18/196,855 US20230289611A1 (en) 2017-09-28 2023-05-12 Locating a decision boundary for complex classifier

Applications Claiming Priority (8)

Application Number Priority Date Filing Date Title
US201762564754P 2017-09-28 2017-09-28
US62/564,754 2017-09-28
PCT/US2018/051069 WO2019067236A1 (fr) 2017-09-28 2018-09-14 Mélange de modèles de générateurs
USPCT/US2018/051069 2018-09-14
PCT/US2018/051332 WO2019067248A1 (fr) 2017-09-28 2018-09-17 Estimation de quantité de dégradation avec un objectif de régression en apprentissage profond
USPCT/US2018/051332 2018-09-17
USPCT/US2018/051683 2018-09-19
PCT/US2018/051683 WO2019067281A1 (fr) 2017-09-28 2018-09-19 Mémoire auto-associative robuste avec réseau de neurones bouclé

Related Parent Applications (1)

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PCT/US2018/051683 Continuation WO2019067281A1 (fr) 2017-09-28 2018-09-19 Mémoire auto-associative robuste avec réseau de neurones bouclé

Related Child Applications (2)

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US16/645,710 A-371-Of-International US20200285939A1 (en) 2017-09-28 2018-09-28 Aggressive development with cooperative generators
US16/901,608 Continuation US11410050B2 (en) 2017-09-28 2020-06-15 Imitation training for machine learning systems with synthetic data generators

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CN110133146A (zh) * 2019-05-28 2019-08-16 国网上海市电力公司 一种考虑不平衡数据样本的变压器故障诊断方法及系统
CN110739030A (zh) * 2019-09-16 2020-01-31 北京化工大学 一种乙烯生产过程小样本的软测量方法
US10832137B2 (en) 2018-01-30 2020-11-10 D5Ai Llc Merging multiple nodal networks
EP3739515A1 (fr) * 2019-05-16 2020-11-18 Robert Bosch GmbH Détermination d'un masque de perturbation pour un modèle de classification
US10885470B2 (en) 2017-06-26 2021-01-05 D5Ai Llc Selective training for decorrelation of errors
CN112215251A (zh) * 2019-07-09 2021-01-12 百度（美国）有限责任公司 用于使用基于特征分散的对抗训练来防御对抗攻击的系统和方法
US10922587B2 (en) 2018-07-03 2021-02-16 D5Ai Llc Analyzing and correcting vulnerabilities in neural networks
US10929757B2 (en) 2018-01-30 2021-02-23 D5Ai Llc Creating and training a second nodal network to perform a subtask of a primary nodal network
CN112416293A (zh) * 2020-11-24 2021-02-26 深圳市人工智能与机器人研究院 一种神经网络增强方法、系统及其应用
US10956818B2 (en) 2017-06-08 2021-03-23 D5Ai Llc Data splitting by gradient direction for neural networks
US20210125005A1 (en) * 2019-10-23 2021-04-29 De-Identification Ltd. System and method for protection and detection of adversarial attacks against a classifier
US11003982B2 (en) 2017-06-27 2021-05-11 D5Ai Llc Aligned training of deep networks
WO2021089570A1 (fr) * 2019-11-08 2021-05-14 Koninklijke Philips N.V. Combinaison de sorties de modèle en une sortie de modèle combinée
US11010670B2 (en) 2018-08-27 2021-05-18 D5Ai Llc Building a deep neural network with diverse strata
US11037059B2 (en) 2018-08-31 2021-06-15 D5Ai Llc Self-supervised back propagation for deep learning
CN112990424A (zh) * 2019-12-17 2021-06-18 杭州海康威视数字技术股份有限公司 神经网络模型训练的方法和装置
US11074502B2 (en) 2018-08-23 2021-07-27 D5Ai Llc Efficiently building deep neural networks
CN113343991A (zh) * 2021-08-02 2021-09-03 四川新网银行股份有限公司 一种特征内增强的弱监督学习方法
WO2021194516A1 (fr) * 2020-03-23 2021-09-30 D5Ai Llc Partage de connaissances de nœud à nœud dépendant de données par régularisation en apprentissage profond
EP3905139A1 (fr) * 2020-04-30 2021-11-03 Stradvision, Inc. Procédé permettant d'effectuer un apprentissage continu sur le classificateur d'un client capable de classer des images au moyen d'un serveur d'apprentissage continu et serveur d'apprentissage continu l'utilisant
US11195097B2 (en) 2018-07-16 2021-12-07 D5Ai Llc Building ensembles for deep learning by parallel data splitting
CN113822437A (zh) * 2020-06-18 2021-12-21 辉达公司 深度分层的变分自动编码器
US20220060235A1 (en) * 2020-08-18 2022-02-24 Qualcomm Incorporated Federated learning for client-specific neural network parameter generation for wireless communication
US11270188B2 (en) 2017-09-28 2022-03-08 D5Ai Llc Joint optimization of ensembles in deep learning
US11295210B2 (en) 2017-06-05 2022-04-05 D5Ai Llc Asynchronous agents with learning coaches and structurally modifying deep neural networks without performance degradation
US11321612B2 (en) 2018-01-30 2022-05-03 D5Ai Llc Self-organizing partially ordered networks and soft-tying learned parameters, such as connection weights
US11410050B2 (en) 2017-09-28 2022-08-09 D5Ai Llc Imitation training for machine learning systems with synthetic data generators
US11501164B2 (en) 2018-08-09 2022-11-15 D5Ai Llc Companion analysis network in deep learning
US11640552B2 (en) 2019-10-01 2023-05-02 International Business Machines Corporation Two stage training to obtain a best deep learning model with efficient use of computing resources
US11676026B2 (en) 2018-06-29 2023-06-13 D5Ai Llc Using back propagation computation as data
CN116843985A (zh) * 2023-09-01 2023-10-03 中国地质调查局武汉地质调查中心 一种基于多重一致性约束的矿区图像半监督分类方法
US11836600B2 (en) 2020-08-20 2023-12-05 D5Ai Llc Targeted incremental growth with continual learning in deep neural networks
US11847559B2 (en) 2020-03-04 2023-12-19 HCL America, Inc. Modifying data cleansing techniques for training and validating an artificial neural network model
CN112990424B (zh) * 2019-12-17 2024-05-10 杭州海康威视数字技术股份有限公司 神经网络模型训练的方法和装置

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Cited By (51)

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US11790235B2 (en) 2017-06-05 2023-10-17 D5Ai Llc Deep neural network with compound node functioning as a detector and rejecter
US11562246B2 (en) 2017-06-05 2023-01-24 D5Ai Llc Asynchronous agents with learning coaches and structurally modifying deep neural networks without performance degradation
US11392832B2 (en) 2017-06-05 2022-07-19 D5Ai Llc Asynchronous agents with learning coaches and structurally modifying deep neural networks without performance degradation
US11295210B2 (en) 2017-06-05 2022-04-05 D5Ai Llc Asynchronous agents with learning coaches and structurally modifying deep neural networks without performance degradation
US10956818B2 (en) 2017-06-08 2021-03-23 D5Ai Llc Data splitting by gradient direction for neural networks
US10885470B2 (en) 2017-06-26 2021-01-05 D5Ai Llc Selective training for decorrelation of errors
US11003982B2 (en) 2017-06-27 2021-05-11 D5Ai Llc Aligned training of deep networks
US11531900B2 (en) 2017-09-28 2022-12-20 D5Ai Llc Imitation learning for machine learning systems with synthetic data generators
US11410050B2 (en) 2017-09-28 2022-08-09 D5Ai Llc Imitation training for machine learning systems with synthetic data generators
US11270188B2 (en) 2017-09-28 2022-03-08 D5Ai Llc Joint optimization of ensembles in deep learning
US11010671B2 (en) 2018-01-30 2021-05-18 D5Ai Llc Iterative training of a nodal network with data influence weights
US11151455B2 (en) 2018-01-30 2021-10-19 D5Ai Llc Counter-tying nodes of a nodal network
US11748624B2 (en) 2018-01-30 2023-09-05 D5Ai Llc Evaluating the value of connecting a selected pair of unconnected nodes of a nodal network
US10832137B2 (en) 2018-01-30 2020-11-10 D5Ai Llc Merging multiple nodal networks
US11461655B2 (en) 2018-01-30 2022-10-04 D5Ai Llc Self-organizing partially ordered networks
US11321612B2 (en) 2018-01-30 2022-05-03 D5Ai Llc Self-organizing partially ordered networks and soft-tying learned parameters, such as connection weights
US10929757B2 (en) 2018-01-30 2021-02-23 D5Ai Llc Creating and training a second nodal network to perform a subtask of a primary nodal network
US11087217B2 (en) 2018-01-30 2021-08-10 D5Ai Llc Directly connecting nodes of different copies on an unrolled recursive neural network
US11093830B2 (en) 2018-01-30 2021-08-17 D5Ai Llc Stacking multiple nodal networks
US11676026B2 (en) 2018-06-29 2023-06-13 D5Ai Llc Using back propagation computation as data
US10922587B2 (en) 2018-07-03 2021-02-16 D5Ai Llc Analyzing and correcting vulnerabilities in neural networks
US11195097B2 (en) 2018-07-16 2021-12-07 D5Ai Llc Building ensembles for deep learning by parallel data splitting
US11501164B2 (en) 2018-08-09 2022-11-15 D5Ai Llc Companion analysis network in deep learning
US11074502B2 (en) 2018-08-23 2021-07-27 D5Ai Llc Efficiently building deep neural networks
US11010670B2 (en) 2018-08-27 2021-05-18 D5Ai Llc Building a deep neural network with diverse strata
US11037059B2 (en) 2018-08-31 2021-06-15 D5Ai Llc Self-supervised back propagation for deep learning
EP3739515A1 (fr) * 2019-05-16 2020-11-18 Robert Bosch GmbH Détermination d'un masque de perturbation pour un modèle de classification
CN110133146A (zh) * 2019-05-28 2019-08-16 国网上海市电力公司 一种考虑不平衡数据样本的变压器故障诊断方法及系统
CN112215251A (zh) * 2019-07-09 2021-01-12 百度（美国）有限责任公司 用于使用基于特征分散的对抗训练来防御对抗攻击的系统和方法
CN110739030A (zh) * 2019-09-16 2020-01-31 北京化工大学 一种乙烯生产过程小样本的软测量方法
CN110739030B (zh) * 2019-09-16 2023-09-01 北京化工大学 一种乙烯生产过程小样本的软测量方法
US11640552B2 (en) 2019-10-01 2023-05-02 International Business Machines Corporation Two stage training to obtain a best deep learning model with efficient use of computing resources
US11762998B2 (en) * 2019-10-23 2023-09-19 De-Identification Ltd. System and method for protection and detection of adversarial attacks against a classifier
US20210125005A1 (en) * 2019-10-23 2021-04-29 De-Identification Ltd. System and method for protection and detection of adversarial attacks against a classifier
WO2021089570A1 (fr) * 2019-11-08 2021-05-14 Koninklijke Philips N.V. Combinaison de sorties de modèle en une sortie de modèle combinée
CN112990424A (zh) * 2019-12-17 2021-06-18 杭州海康威视数字技术股份有限公司 神经网络模型训练的方法和装置
CN112990424B (zh) * 2019-12-17 2024-05-10 杭州海康威视数字技术股份有限公司 神经网络模型训练的方法和装置
US11847559B2 (en) 2020-03-04 2023-12-19 HCL America, Inc. Modifying data cleansing techniques for training and validating an artificial neural network model
WO2021194516A1 (fr) * 2020-03-23 2021-09-30 D5Ai Llc Partage de connaissances de nœud à nœud dépendant de données par régularisation en apprentissage profond
US11741340B2 (en) 2020-03-23 2023-08-29 D5Ai Llc Data-dependent node-to-node knowledge sharing by regularization in deep learning
WO2021221254A1 (fr) * 2020-04-30 2021-11-04 StradVision, Inc. Procédé pour effectuer à l'aide d'un serveur d'apprentissage continu un apprentissage continu sur un classifieur dans un client apte à classifier des images, et serveur d'apprentissage continu l'utilisant
EP3905139A1 (fr) * 2020-04-30 2021-11-03 Stradvision, Inc. Procédé permettant d'effectuer un apprentissage continu sur le classificateur d'un client capable de classer des images au moyen d'un serveur d'apprentissage continu et serveur d'apprentissage continu l'utilisant
CN113822437A (zh) * 2020-06-18 2021-12-21 辉达公司 深度分层的变分自动编码器
US20220060235A1 (en) * 2020-08-18 2022-02-24 Qualcomm Incorporated Federated learning for client-specific neural network parameter generation for wireless communication
US11909482B2 (en) * 2020-08-18 2024-02-20 Qualcomm Incorporated Federated learning for client-specific neural network parameter generation for wireless communication
US11836600B2 (en) 2020-08-20 2023-12-05 D5Ai Llc Targeted incremental growth with continual learning in deep neural networks
US11948063B2 (en) 2020-08-20 2024-04-02 D5Ai Llc Improving a deep neural network with node-to-node relationship regularization
CN112416293A (zh) * 2020-11-24 2021-02-26 深圳市人工智能与机器人研究院 一种神经网络增强方法、系统及其应用
CN113343991A (zh) * 2021-08-02 2021-09-03 四川新网银行股份有限公司 一种特征内增强的弱监督学习方法
CN116843985A (zh) * 2023-09-01 2023-10-03 中国地质调查局武汉地质调查中心 一种基于多重一致性约束的矿区图像半监督分类方法
CN116843985B (zh) * 2023-09-01 2023-11-17 中国地质调查局武汉地质调查中心 一种基于多重一致性约束的矿区图像半监督分类方法

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