CA3097036A1 - Selecting a neural network architecture for a supervised machine learning problem - Google Patents

Selecting a neural network architecture for a supervised machine learning problem Download PDF

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Publication number
CA3097036A1
CA3097036A1 CA3097036A CA3097036A CA3097036A1 CA 3097036 A1 CA3097036 A1 CA 3097036A1 CA 3097036 A CA3097036 A CA 3097036A CA 3097036 A CA3097036 A CA 3097036A CA 3097036 A1 CA3097036 A1 CA 3097036A1
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neural network
machine learning
learning problem
measure
candidate neural
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CA3097036A
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English (en)
French (fr)
Inventor
Saeed AMIZADEH
Ge Yang
Nicolo Fusi
Francesco Paolo CASALE
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Microsoft Technology Licensing LLC
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Microsoft Technology Licensing LLC
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    • 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
    • G06N3/09—Supervised 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
    • G06N3/0464—Convolutional networks [CNN, ConvNet]
    • 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
    • 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
    • G06N3/044—Recurrent networks, e.g. Hopfield 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
    • G06N3/045—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
    • G06N3/047—Probabilistic or stochastic 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
    • G06N3/0499—Feedforward 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
    • G06N3/08—Learning methods
    • G06N3/082—Learning methods modifying the architecture, e.g. adding, deleting or silencing nodes or connections
    • 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
    • G06N3/084—Backpropagation, e.g. using gradient descent
    • 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
    • G06N3/0985—Hyperparameter optimisation; Meta-learning; Learning-to-learn
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N5/00—Computing arrangements using knowledge-based models
    • G06N5/04—Inference or reasoning models
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N20/00—Machine learning
    • G06N20/10—Machine learning using kernel methods, e.g. support vector machines [SVM]
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N5/00—Computing arrangements using knowledge-based models
    • G06N5/01—Dynamic search techniques; Heuristics; Dynamic trees; Branch-and-bound

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  • Engineering & Computer Science (AREA)
  • Physics & Mathematics (AREA)
  • Theoretical Computer Science (AREA)
  • Software Systems (AREA)
  • Computing Systems (AREA)
  • Artificial Intelligence (AREA)
  • Mathematical Physics (AREA)
  • Data Mining & Analysis (AREA)
  • Evolutionary Computation (AREA)
  • General Physics & Mathematics (AREA)
  • General Engineering & Computer Science (AREA)
  • Computational Linguistics (AREA)
  • Biophysics (AREA)
  • Molecular Biology (AREA)
  • General Health & Medical Sciences (AREA)
  • Biomedical Technology (AREA)
  • Life Sciences & Earth Sciences (AREA)
  • Health & Medical Sciences (AREA)
  • Probability & Statistics with Applications (AREA)
  • Information Retrieval, Db Structures And Fs Structures Therefor (AREA)
  • Management, Administration, Business Operations System, And Electronic Commerce (AREA)
  • Complex Calculations (AREA)
  • Image Analysis (AREA)
  • Debugging And Monitoring (AREA)
  • Computer Vision & Pattern Recognition (AREA)
  • Medical Informatics (AREA)
CA3097036A 2018-05-10 2019-04-27 Selecting a neural network architecture for a supervised machine learning problem Pending CA3097036A1 (en)

Applications Claiming Priority (3)

Application Number Priority Date Filing Date Title
US15/976,514 2018-05-10
US15/976,514 US11995538B2 (en) 2018-05-10 2018-05-10 Selecting a neural network architecture for a supervised machine learning problem
PCT/US2019/029532 WO2019217113A1 (en) 2018-05-10 2019-04-27 Selecting a neural network architecture for a supervised machine learning problem

Publications (1)

Publication Number Publication Date
CA3097036A1 true CA3097036A1 (en) 2019-11-14

Family

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Application Number Title Priority Date Filing Date
CA3097036A Pending CA3097036A1 (en) 2018-05-10 2019-04-27 Selecting a neural network architecture for a supervised machine learning problem

Country Status (6)

Country Link
US (3) US11995538B2 (enExample)
EP (1) EP3791326A1 (enExample)
JP (1) JP7344900B2 (enExample)
CN (2) CN120297334A (enExample)
CA (1) CA3097036A1 (enExample)
WO (1) WO2019217113A1 (enExample)

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CN111819580B (zh) * 2018-05-29 2025-01-14 谷歌有限责任公司 用于密集图像预测任务的神经架构搜索
US11537846B2 (en) * 2018-08-21 2022-12-27 Wisconsin Alumni Research Foundation Neural network architecture with concurrent uncertainty output
KR102200212B1 (ko) * 2018-12-07 2021-01-08 서울대학교 산학협력단 불확실성 예측을 위한 샘플링 모델 생성 장치 및 방법, 불확실성 예측 장치
US10616257B1 (en) * 2019-02-19 2020-04-07 Verizon Patent And Licensing Inc. Method and system for anomaly detection and network deployment based on quantitative assessment
US11240340B2 (en) * 2020-05-12 2022-02-01 International Business Machines Corporation Optimized deployment of analytic models in an edge topology
CN113807376A (zh) * 2020-06-15 2021-12-17 富泰华工业（深圳）有限公司 网络模型优化方法、装置、电子设备及存储介质
CN112134876A (zh) * 2020-09-18 2020-12-25 中移（杭州）信息技术有限公司 流量识别系统及方法、服务器
KR102535007B1 (ko) * 2020-11-13 2023-05-19 숭실대학교 산학협력단 Snn 모델 파라미터를 기반으로 모델 수행을 위한 뉴로모픽 아키텍처 동적 선택 방법, 이를 수행하기 위한 기록 매체 및 장치
US20220164646A1 (en) * 2020-11-24 2022-05-26 EMC IP Holding Company LLC Hydratable neural networks for devices
CN113204916B (zh) * 2021-04-15 2021-11-19 特斯联科技集团有限公司 基于强化学习的智能决策方法及系统
US20220027792A1 (en) * 2021-10-08 2022-01-27 Intel Corporation Deep neural network model design enhanced by real-time proxy evaluation feedback
US12367249B2 (en) * 2021-10-19 2025-07-22 Intel Corporation Framework for optimization of machine learning architectures
US12367248B2 (en) * 2021-10-19 2025-07-22 Intel Corporation Hardware-aware machine learning model search mechanisms
US12417260B2 (en) 2021-10-20 2025-09-16 Intel Corporation Machine learning model scaling system with energy efficient network data transfer for power aware hardware
CN114037058B (zh) * 2021-11-05 2024-05-17 北京百度网讯科技有限公司 预训练模型的生成方法、装置、电子设备以及存储介质
CN114188022A (zh) * 2021-12-13 2022-03-15 浙江大学 一种基于TextCNN模型的临床儿童咳嗽智能预诊断系统

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Also Published As

Publication number Publication date
US20190347548A1 (en) 2019-11-14
EP3791326A1 (en) 2021-03-17
CN120297334A (zh) 2025-07-11
US20250390745A1 (en) 2025-12-25
US20240273370A1 (en) 2024-08-15
CN112470171B (zh) 2025-04-18
US11995538B2 (en) 2024-05-28
CN112470171A (zh) 2021-03-09
JP2021523430A (ja) 2021-09-02
KR20210008480A (ko) 2021-01-22
JP7344900B2 (ja) 2023-09-14
WO2019217113A1 (en) 2019-11-14
US12423581B2 (en) 2025-09-23

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