JP2018518740A - バイアス項を介して深層ニューラルネットワーク中にトップダウン情報を組み込むこと - Google Patents

バイアス項を介して深層ニューラルネットワーク中にトップダウン情報を組み込むこと Download PDF

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JP2018518740A
JP2018518740A JP2017556147A JP2017556147A JP2018518740A JP 2018518740 A JP2018518740 A JP 2018518740A JP 2017556147 A JP2017556147 A JP 2017556147A JP 2017556147 A JP2017556147 A JP 2017556147A JP 2018518740 A JP2018518740 A JP 2018518740A
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トワル、レーガン・ブライス
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Qualcomm Inc
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    • 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
    • G06N3/048—Activation functions
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N7/00—Computing arrangements based on specific mathematical models
    • G06N7/01—Probabilistic graphical models, e.g. probabilistic networks

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JP2017556147A 2015-04-28 2016-03-11 バイアス項を介して深層ニューラルネットワーク中にトップダウン情報を組み込むこと Pending JP2018518740A (ja)

Applications Claiming Priority (5)

Application Number Priority Date Filing Date Title
US201562154097P 2015-04-28 2015-04-28
US62/154,097 2015-04-28
US14/848,288 2015-09-08
US14/848,288 US10325202B2 (en) 2015-04-28 2015-09-08 Incorporating top-down information in deep neural networks via the bias term
PCT/US2016/022158 WO2016175925A1 (en) 2015-04-28 2016-03-11 Incorporating top-down information in deep neural networks via the bias term

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JP2018518740A true JP2018518740A (ja) 2018-07-12
JP2018518740A5 JP2018518740A5 (enExample) 2019-04-04

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US (1) US10325202B2 (enExample)
EP (1) EP3289527A1 (enExample)
JP (1) JP2018518740A (enExample)
KR (1) KR20170140228A (enExample)
CN (1) CN107533665A (enExample)
AU (1) AU2016256315A1 (enExample)
BR (1) BR112017022983A2 (enExample)
WO (1) WO2016175925A1 (enExample)

Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JP2022008236A (ja) * 2020-06-24 2022-01-13 三星電子株式会社 ニューロモルフィック装置及びニューラルネットワークを具現する方法

Families Citing this family (19)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
FR3044438A1 (fr) * 2015-11-27 2017-06-02 Thales Sa Systeme et procede d'aide a la decision
WO2018035805A1 (en) * 2016-08-25 2018-03-01 Intel Corporation Coupled multi-task fully convolutional networks using multi-scale contextual information and hierarchical hyper-features for semantic image segmentation
CA3051990C (en) * 2017-02-23 2021-03-23 Cerebras Systems Inc. Accelerated deep learning
US11842280B2 (en) 2017-05-05 2023-12-12 Nvidia Corporation Loss-scaling for deep neural network training with reduced precision
WO2018218651A1 (en) 2017-06-02 2018-12-06 Nokia Technologies Oy Artificial neural network
US10108538B1 (en) 2017-07-31 2018-10-23 Google Llc Accessing prologue and epilogue data
US11144815B2 (en) * 2017-12-04 2021-10-12 Optimum Semiconductor Technologies Inc. System and architecture of neural network accelerator
KR102153791B1 (ko) * 2017-12-20 2020-09-08 연세대학교 산학협력단 인공 신경망을 위한 디지털 뉴런, 인공 뉴런 및 이를 포함하는 추론 엔진
US11531930B2 (en) * 2018-03-12 2022-12-20 Royal Bank Of Canada System and method for monitoring machine learning models
CN108977897B (zh) * 2018-06-07 2021-11-19 浙江天悟智能技术有限公司 基于局部内在可塑性回声状态网络的熔纺工艺控制方法
US20210350236A1 (en) * 2018-09-28 2021-11-11 National Technology & Engineering Solutions Of Sandia, Llc Neural network robustness via binary activation
KR102184655B1 (ko) * 2018-10-29 2020-11-30 에스케이텔레콤 주식회사 비대칭 tanh 활성 함수를 이용한 예측 성능의 개선
US11481667B2 (en) * 2019-01-24 2022-10-25 International Business Machines Corporation Classifier confidence as a means for identifying data drift
US20200242771A1 (en) * 2019-01-25 2020-07-30 Nvidia Corporation Semantic image synthesis for generating substantially photorealistic images using neural networks
DE102019217444A1 (de) * 2019-11-12 2021-05-12 Robert Bosch Gmbh Verfahren und Vorrichtung zur Klassifizierung digitaler Bilddaten
US10929748B1 (en) * 2019-11-26 2021-02-23 Mythic, Inc. Systems and methods for implementing operational transformations for restricted computations of a mixed-signal integrated circuit
US12154032B2 (en) * 2020-02-04 2024-11-26 Dsp Group Ltd. Post-training control of the bias of neural networks
US12216740B2 (en) 2021-01-08 2025-02-04 Bank Of America Corporation Data source evaluation platform for improved generation of supervised learning models
CN113473580B (zh) * 2021-05-14 2024-04-26 南京信息工程大学滨江学院 异构网络中基于深度学习的用户关联联合功率分配方法

Citations (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JP2000112914A (ja) * 1998-10-09 2000-04-21 Toshiba Corp 神経回路網の学習方法

Family Cites Families (7)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO2008066731A2 (en) 2006-11-22 2008-06-05 Psigenics Corporation Device and method responsive to influences of mind
WO2010030794A1 (en) 2008-09-10 2010-03-18 Digital Infuzion, Inc. Machine learning methods and systems for identifying patterns in data
US8239336B2 (en) 2009-03-09 2012-08-07 Microsoft Corporation Data processing using restricted boltzmann machines
US8754802B2 (en) 2010-08-26 2014-06-17 Lawrence Livermore National Security, Llc Determining root correspondence between previously and newly detected objects
US20150019468A1 (en) 2013-07-09 2015-01-15 Knowmtech, Llc Thermodynamic computing
CN103778414A (zh) * 2014-01-17 2014-05-07 杭州电子科技大学 基于深度神经网络的实时人脸识别方法
CN104200224A (zh) * 2014-08-28 2014-12-10 西北工业大学 基于深度卷积神经网络的无价值图像去除方法

Patent Citations (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JP2000112914A (ja) * 1998-10-09 2000-04-21 Toshiba Corp 神経回路網の学習方法

Non-Patent Citations (1)

* Cited by examiner, † Cited by third party
Title
SHAOFEI XUE ET AL.: ""DIRECT ADAPTATION OF HYBRID DNN/HMM MODEL FOR FAST SPEAKER ADAPTATION IN LVCSR BASED ON SPEAKER COD", 2014 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH AND SIGNAL PROCESSING (ICASSP), JPN6020003276, 2014, US, pages 6339 - 6343, ISSN: 0004204518 *

Cited By (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JP2022008236A (ja) * 2020-06-24 2022-01-13 三星電子株式会社 ニューロモルフィック装置及びニューラルネットワークを具現する方法
JP7776214B2 (ja) 2020-06-24 2025-11-26 三星電子株式会社 ニューロモルフィック装置及びニューラルネットワークを具現する方法

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WO2016175925A1 (en) 2016-11-03
US10325202B2 (en) 2019-06-18
US20160321542A1 (en) 2016-11-03
KR20170140228A (ko) 2017-12-20
EP3289527A1 (en) 2018-03-07
AU2016256315A1 (en) 2017-10-05
BR112017022983A2 (pt) 2018-07-24
CN107533665A (zh) 2018-01-02

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