KR102793134B1 - 컨볼루션 신경망의 가지-치기 및 재훈련 방법 - Google Patents
컨볼루션 신경망의 가지-치기 및 재훈련 방법 Download PDFInfo
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- KR102793134B1 KR102793134B1 KR1020180105880A KR20180105880A KR102793134B1 KR 102793134 B1 KR102793134 B1 KR 102793134B1 KR 1020180105880 A KR1020180105880 A KR 1020180105880A KR 20180105880 A KR20180105880 A KR 20180105880A KR 102793134 B1 KR102793134 B1 KR 102793134B1
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- G06—COMPUTING OR CALCULATING; COUNTING
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- G06N3/00—Computing arrangements based on biological models
- G06N3/02—Neural networks
- G06N3/08—Learning methods
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- 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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- G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N3/00—Computing arrangements based on biological models
- G06N3/02—Neural networks
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- G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
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- G06N3/045—Combinations of networks
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- 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]
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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
- G06N3/04—Architecture, e.g. interconnection topology
- G06N3/0495—Quantised networks; Sparse networks; Compressed networks
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- G—PHYSICS
- G06—COMPUTING OR CALCULATING; COUNTING
- G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
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Applications Claiming Priority (2)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| US15/699,438 | 2017-09-08 | ||
| US15/699,438 US11200495B2 (en) | 2017-09-08 | 2017-09-08 | Pruning and retraining method for a convolution neural network |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| KR20190028320A KR20190028320A (ko) | 2019-03-18 |
| KR102793134B1 true KR102793134B1 (ko) | 2025-04-07 |
Family
ID=63490311
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| KR1020180105880A Active KR102793134B1 (ko) | 2017-09-08 | 2018-09-05 | 컨볼루션 신경망의 가지-치기 및 재훈련 방법 |
Country Status (5)
| Country | Link |
|---|---|
| US (1) | US11200495B2 (https=) |
| EP (1) | EP3454262A1 (https=) |
| JP (1) | JP7232599B2 (https=) |
| KR (1) | KR102793134B1 (https=) |
| CN (1) | CN109472357A (https=) |
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| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US11734568B2 (en) * | 2018-02-14 | 2023-08-22 | Google Llc | Systems and methods for modification of neural networks based on estimated edge utility |
| KR20200023238A (ko) * | 2018-08-23 | 2020-03-04 | 삼성전자주식회사 | 딥러닝 모델을 생성하는 방법 및 시스템 |
| CN111738401A (zh) * | 2019-03-25 | 2020-10-02 | 北京三星通信技术研究有限公司 | 模型优化方法、分组压缩方法、相应的装置、设备 |
| US12373696B2 (en) * | 2019-06-21 | 2025-07-29 | Samsung Electronics Co., Ltd. | Neural network hardware accelerator system with zero-skipping and hierarchical structured pruning methods |
| US20210089921A1 (en) * | 2019-09-25 | 2021-03-25 | Nvidia Corporation | Transfer learning for neural networks |
| US11704571B2 (en) * | 2019-10-11 | 2023-07-18 | Qualcomm Incorporated | Learned threshold pruning for deep neural networks |
| CN112699990B (zh) * | 2019-10-22 | 2024-06-07 | 杭州海康威视数字技术股份有限公司 | 神经网络模型训练方法、装置及电子设备 |
| CN111061909B (zh) * | 2019-11-22 | 2023-11-28 | 腾讯音乐娱乐科技(深圳)有限公司 | 一种伴奏分类方法和装置 |
| US11935271B2 (en) * | 2020-01-10 | 2024-03-19 | Tencent America LLC | Neural network model compression with selective structured weight unification |
| US11562235B2 (en) | 2020-02-21 | 2023-01-24 | International Business Machines Corporation | Activation function computation for neural networks |
| CN111582456B (zh) * | 2020-05-11 | 2023-12-15 | 抖音视界有限公司 | 用于生成网络模型信息的方法、装置、设备和介质 |
| WO2021248409A1 (en) * | 2020-06-11 | 2021-12-16 | Alibaba Group Holding Limited | Pruning hardware unit for training neural network |
| CN111553169B (zh) * | 2020-06-25 | 2023-08-25 | 北京百度网讯科技有限公司 | 语义理解模型的剪枝方法、装置、电子设备和存储介质 |
| CN111539224B (zh) * | 2020-06-25 | 2023-08-25 | 北京百度网讯科技有限公司 | 语义理解模型的剪枝方法、装置、电子设备和存储介质 |
| US12488250B2 (en) | 2020-11-02 | 2025-12-02 | International Business Machines Corporation | Weight repetition on RPU crossbar arrays |
| US20220156574A1 (en) * | 2020-11-19 | 2022-05-19 | Kabushiki Kaisha Toshiba | Methods and systems for remote training of a machine learning model |
| US20220318633A1 (en) * | 2021-03-26 | 2022-10-06 | Qualcomm Incorporated | Model compression using pruning quantization and knowledge distillation |
| US20220405571A1 (en) * | 2021-06-16 | 2022-12-22 | Microsoft Technology Licensing, Llc | Sparsifying narrow data formats for neural networks |
| CN113469326B (zh) * | 2021-06-24 | 2024-04-02 | 上海寒武纪信息科技有限公司 | 在神经网络模型中执行剪枝优化的集成电路装置及板卡 |
| US12524673B2 (en) * | 2021-07-16 | 2026-01-13 | Industry-Academic Cooperation Foundation, Yonsei University | Multitask distributed learning system and method based on lottery ticket neural network |
| JP7666289B2 (ja) | 2021-10-25 | 2025-04-22 | 富士通株式会社 | 機械学習プログラム、機械学習方法、及び、情報処理装置 |
| US12591778B2 (en) | 2021-11-17 | 2026-03-31 | Samsung Electronics Co., Ltd. | System and method for torque-based structured pruning for deep neural networks |
| CN115115045B (zh) * | 2021-12-24 | 2026-02-06 | 杭州海康威视数字技术股份有限公司 | 一种模型剪枝方法、装置及电子设备 |
| CN114462582A (zh) * | 2022-02-25 | 2022-05-10 | 腾讯科技(深圳)有限公司 | 基于卷积神经网络模型的数据处理方法及装置、设备 |
| JP7782319B2 (ja) | 2022-03-04 | 2025-12-09 | 富士通株式会社 | 機械学習プログラム、機械学習方法、及び、情報処理装置 |
| CN120562503A (zh) * | 2022-03-31 | 2025-08-29 | 支付宝(杭州)信息技术有限公司 | 模型剪枝方法、装置和计算机设备 |
| CN114863243B (zh) * | 2022-04-28 | 2024-12-17 | 国家电网有限公司大数据中心 | 一种模型的数据遗忘方法、装置、设备及存储介质 |
| US20240013050A1 (en) * | 2022-07-05 | 2024-01-11 | International Business Machines Corporation | Packing machine learning models using pruning and permutation |
| US12524999B2 (en) * | 2022-09-30 | 2026-01-13 | Samsung Electronics Co., Ltd. | Generating images with small objects for training a pruned super-resolution network |
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| Publication number | Priority date | Publication date | Assignee | Title |
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| US5288645A (en) * | 1992-09-04 | 1994-02-22 | Mtm Engineering, Inc. | Hydrogen evolution analyzer |
| JP5234085B2 (ja) | 2010-11-11 | 2013-07-10 | 富士電機株式会社 | ニューラルネットワークの学習方法 |
| US10373054B2 (en) | 2015-04-19 | 2019-08-06 | International Business Machines Corporation | Annealed dropout training of neural networks |
| US11423311B2 (en) * | 2015-06-04 | 2022-08-23 | Samsung Electronics Co., Ltd. | Automatic tuning of artificial neural networks |
| US10832136B2 (en) * | 2016-05-18 | 2020-11-10 | Nec Corporation | Passive pruning of filters in a convolutional neural network |
| US10832123B2 (en) * | 2016-08-12 | 2020-11-10 | Xilinx Technology Beijing Limited | Compression of deep neural networks with proper use of mask |
| US10984308B2 (en) * | 2016-08-12 | 2021-04-20 | Xilinx Technology Beijing Limited | Compression method for deep neural networks with load balance |
| US10762426B2 (en) * | 2016-08-12 | 2020-09-01 | Beijing Deephi Intelligent Technology Co., Ltd. | Multi-iteration compression for deep neural networks |
| JP6729455B2 (ja) | 2017-03-15 | 2020-07-22 | 株式会社島津製作所 | 分析データ解析装置及び分析データ解析方法 |
| CN107688850B (zh) * | 2017-08-08 | 2021-04-13 | 赛灵思公司 | 一种深度神经网络压缩方法 |
-
2017
- 2017-09-08 US US15/699,438 patent/US11200495B2/en active Active
-
2018
- 2018-09-03 EP EP18192220.4A patent/EP3454262A1/en not_active Withdrawn
- 2018-09-05 JP JP2018165782A patent/JP7232599B2/ja active Active
- 2018-09-05 KR KR1020180105880A patent/KR102793134B1/ko active Active
- 2018-09-10 CN CN201811051626.XA patent/CN109472357A/zh active Pending
Non-Patent Citations (1)
| Title |
|---|
| Song Han et al., "Learning bothWeights and Connections for Efficient Neural Networks," arXiv:1506.02626v3 [cs.NE] 30 Oct 2015 (2015.10.30.)* |
Also Published As
| Publication number | Publication date |
|---|---|
| US20190080238A1 (en) | 2019-03-14 |
| KR20190028320A (ko) | 2019-03-18 |
| JP7232599B2 (ja) | 2023-03-03 |
| EP3454262A1 (en) | 2019-03-13 |
| US11200495B2 (en) | 2021-12-14 |
| CN109472357A (zh) | 2019-03-15 |
| JP2019049977A (ja) | 2019-03-28 |
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