博士(工学), 金沢大学, Mar. 1997

Doctor of Engineering, Kanazawa University, Mar. 1997

On-line learning

On-line Learning theory

Informational Statistical Mechanics

Neural Networks

Deep Learning

ensemble-learning

perceptron

Texture analysis

stereoscopic

Informatics, Soft computing, Deep Learning

Informatics, Sensitivity (kansei) informatics, Sensitivity Informatics/Soft Computing

Apr. 1998 - Mar. 2010
Tokyo Metropolitan College of Technology/Professor, ものづくり工学科, Professor

Oct. 1992 - Mar. 1997
Kanazawa University, Graduate School, Division of National Science and Technology (except Gakushuin University, Konan University), System science

Apr. 1979 - Mar. 1981
Nihon University, Graduate School, Division of Industrial Technology, Electrical and Electronics Engineering

Apr. 1975 - Mar. 1979
Nihon University, Faculty of Industrial Technology, Department of Electrical Engineering

Apr. 2021 - Mar. 2025
情報・システムソサエティ英文論文誌編集委員, 電子情報通信学会

Apr. 2007 - Mar. 2011
理事, 日本神経回路学会

The Institute of Electronics, Information andCommunication Engineers, 2020年LOIS研究賞
マルチエージェントシミュレーションによるCOVID19接触確認アプリ COCOAの感染者数削減効果の検証, Official journal
大前佑斗、豊谷純、原一之、権寧博、高橋弘毅

Joint 7th International Conference on Soft Computing and Intelligent Systems and 15th International Symposium on Advanced Intelligent Systems, Best Poster Award
Mutual Leraning for Nonlinear Perceptron, International society
Daisuke Saitoh;Kazuyuki Hara

★Analysis of Function of Rectified Linear Unit Used in Deep learning
Kazuyuki Hara; Daisuke Saito; and Hayaru Shouno
2015 Internation Joint Conference on Neural Networks, Jul. 2015, Refereed, Not invited
Lead

Theoretical Analysis of the SIRVVD Model for Insights Into the Target Rate of COVID-19/SARS-CoV-2 Vaccination in Japan
Yuto Omae; Makoto Sasaki; Jun Toyotani; Kazuyuki Hara; Hirotaka Takahashi
IEEE Access, 2022

Impact of removal strategies of stay-at-home,orders on the number of COVID-19 infectors and people leaving their,homes,
Yuto Omae; Yohei Kakimoto; Jun Toyotani; Kazuyuki Hara; Yasuhiro Gon; Hirotaka Takahashi
International Journal of Innovative Computing, Information and,Control, 2021, Refereed, Not invited

Node-perturbation Learning Applied,for Soft-committee Machine
Kazuyuki Hara; Kentaro Katahira; Masato Okada
IPSJ Transactions on Mathematical Modeling and Its Applications, Aug. 2020, Refereed, Not invited
Lead

A Prediction Method for Viral Disease Outbreak Using a Multi-Agent Simulation Including Capacity Limitation for Isolation Wards and Stay-at-Home Orders
大前 佑斗; 豊谷 純; 原 一之; 高橋 弘毅
知能と情報, 2020, Refereed, Not invited

Analysis of Conventional Dropout and its Application to Group Dropout
Kazuyuki Hara; Daisuke Saitoh; Satoshi Suzuki; Takumi Kondou; and Hayaru Shono
IPSJ transaction on Mathematical Modeling and Its Applications, Jul. 2017, Refereed, Not invited
Lead

Statistical Mechanics of Node-perturbation Learning with Noisy Baseline
Kazuyuki Hara; Kentaro Katahira; Masato Okada
JOURNAL OF THE PHYSICAL SOCIETY OF JAPAN, Feb. 2017, Refereed, Not invited

Group Dropout Inspired by Ensemble Learning
Kazuyuki Hara; Daisuke Saitoh; Takumi Kondou; Satoshi Suzuki; Hayaru Shouno
Lecture Notes in Computer Science, Proc. of ICONIP, Nov. 2016, Refereed, Not invited

22aBT-7 Study on role of dropout as a regularizer
Kondou T.; Suzuki S.; Saitoh D.; Hara K.; Shouno H.
Meeting Abstracts of the Physical Society of Japan, 2016

Analysis of Dropout Learning Regarded as Ensemble Learning
Kazuyuki Hara; Daisuke Saitoh; Hayaru Shouno
ARTIFICIAL NEURAL NETWORKS AND MACHINE LEARNING - ICANN 2016, PT II, 2016, Refereed, Not invited

Mutual Learning using Nonlinear Perceptron
Daisuke Saitoh; Kazuyuki Hara
Journal of Artificial Intelligence and Soft Computing Research, Apr. 2015, Refereed, Invited
Last

22aBL-1 Study on convergence property of on-line learning using convolution network
Saito Daisuke; Hara Kazuyuki; Shouno Hayaru
Meeting Abstracts of the Physical Society of Japan, 2015

Improving the convergence property of soft committee machines by replacing derivative with truncated gaussian function
Kazuyuki Hara; Kentaro Katahira
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2014, Refereed, Not invited

Theoretical analysis of learning speed in gradient descent algorithm replacing derivative with constant
Kazuyuki Hara; Kentaro Katahira
IPSJ Online Transactions, 2014, Refereed, Not invited

Soft Committee Machine Using Simple Derivative Term
Kazuyuki Hara; Kentaro Katahira
ARTIFICIAL INTELLIGENCE AND SOFT COMPUTING ICAISC 2014, PT I, 2014, Refereed, Not invited

Mutual Learning Using Nonlinear Perceptron
Daisuke Saitoh; Kazuyuki Hara
2014 JOINT 7TH INTERNATIONAL CONFERENCE ON SOFT COMPUTING AND INTELLIGENT SYSTEMS (SCIS) AND 15TH INTERNATIONAL SYMPOSIUM ON ADVANCED INTELLIGENT SYSTEMS (ISIS), 2014, Refereed, Not invited

Theoretical analysis of learning speed in gradient descent algorithm replacing derivative with constant
Kazuyuki Hara amd Kentaro Katahira
Information Processing Society of Japan Transactions on Mathematical Modeling and Its Applications, Dec. 2013, Refereed, Not invited
Lead

Statistical mechanics of node-perturbation learning for nonlinear perceptron
Kazuyuki Hara; Kentaro Katahira; Kazuo Okanoya; Masato Okada
Journal of the Physical Society of Japan, May 2013, Refereed, Not invited

Statistical Mechanics of On-line Ensemble Teacher Learning through a Novel Perceptron Learning Rule
Kazuyuki Hara; Seiji Miyoshi
JOURNAL OF THE PHYSICAL SOCIETY OF JAPAN, Jun. 2012, Refereed, Not invited

Theoretical analysis of function of derivative term in on-line gradient descent learning
Kazuyuki Hara; Kentaro Katahira; Kazuo Okanoya; Masato Okada
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2012, Refereed, Not invited

Ensemble-Teacher Learning through a Perceptron Rule with a Margin
Kazuyuki Hara; Seiji Miyoshi
ARTIFICIAL NEURAL NETWORKS AND MACHINE LEARNING - ICANN 2011, PT I, 2011, Refereed, Not invited

Statistical Mechanics of On-line Node-perturbation Learning
Kentaro Katahira; Kazuo Okanoya; Masato Okada
Information Processing Society of Japan Transactions on Mathematical Modeling and Its Applications, Jan. 2011, Refereed, Not invited
Lead

On-Line Ensemble-Teacher Learning through a Perceptron Rule with a Margin
Kazuyuki Hara; Katsuya Ono; Seiji Miyoshi
ARTIFICIAL NEURAL NETWORKS (ICANN 2010), PT III, 2010, Refereed, Not invited

Statistical Mechanics of On-Line Mutual Learning with Many Linear Perceptrons
Kazuyuki Hara; Yoichi Nakayama; Seiji Miyoshi; Masato Okada
JOURNAL OF THE PHYSICAL SOCIETY OF JAPAN, Nov. 2009, Refereed, Not invited

Analysis of Ising Spin Neural Network with Time-Dependent Mexican-Hat-Type Interaction
Kazuyuki Hara; Seiji Miyoshi; Tatsuya Uezu; Masato Okada
ADVANCES IN NEURO-INFORMATION PROCESSING, PT II, 2009, Refereed, Not invited

Mutual Learning with Many Linear Perceptrons: On-Line Learning Theory
Kazuyuki Hara; Yoichi Nakayama; Seiji Miyoshi; Masato Okada
ARTIFICIAL NEURAL NETWORKS - ICANN 2009, PT I, 2009, Refereed, Not invited

Optimization of the asymptotic property of mutual learning involving an integration mechanism of ensemble learning
Kazuyuki Hara; Takahiro Yamada
JOURNAL OF THE PHYSICAL SOCIETY OF JAPAN, Feb. 2008, Refereed, Not invited

Statistical mechanics of mutual learning with a latent teacher
Kazuyuki Hara; Masato Okada
JOURNAL OF THE PHYSICAL SOCIETY OF JAPAN, Jan. 2007, Refereed, Not invited

Analysis of ensemble learning using simple perceptrons based on on-line learning theory
Seiji Miyoshi; Kazuyuki Hara; Masato Okada
Systems and Computers in Japan, Nov. 2005, Refereed, Not invited

Ensemble Learning of Linear Perceptrons: On-Line Learning Theory
Masato Okada
Journal of the Physical Society of Japan, Nov. 2005, Refereed, Not invited
Lead

Analysis of ensemble learning using simple perceptrons based on online learning theory
S Miyoshi; K Hara; M Okada
PHYSICAL REVIEW E, Mar. 2005, Refereed, Not invited

Analysis of ensemble learning using simple perceptrons based on online learning theory
S Miyoshi; K Hara; M Okada
PROGRESS OF THEORETICAL PHYSICS SUPPLEMENT, 2005, Refereed, Not invited

On-line leaning of a simple perceptron learning with margin.
Kazuyuki Hara; Masato Okada
Margin Systems and Computers in Japan, Jun. 2004, Refereed, Not invited

On-line learning through simple perceptron learning with a margin
K Hara; M Okada
NEURAL NETWORKS, Mar. 2004, Refereed, Not invited

Online learning theory of ensemble learning using linear perceptrons
Kazuyuki Hara; Masato Okada
IEEE International Conference on Neural Networks - Conference Proceedings, 2004, Refereed, Not invited

On-line learning through simple perceptron learning with a margin
K Hara; M Okada
ICONIP'02: PROCEEDINGS OF THE 9TH INTERNATIONAL CONFERENCE ON NEURAL INFORMATION PROCESSING, 2002, Refereed, Not invited

階層形神経回路網と線形信号処理法の信号分類能力の比較
原一之; 中山謙二
情報処理学会論文誌, 1997, Refereed, Not invited
Lead

パーシャルアニーリングの統計力学 : 相互作用がメキシカンハット型の場合(ハードウェア(2),ニューロハードウェア,一般)
原 一之; 上江洌 達也; 三好 誠司; 岡田 真人
電子情報通信学会技術研究報告. NC, ニューロコンピューティング, 31 Oct. 2008, Not refereed, Not invited

22pVC-6 メキシカンハット型相互作用が時間変化する系のレプリカ解析II(22pVC 情報統計力学,領域11(統計力学,物性基礎論,応用数学,力学,流体物理))
原 一之; 上江洌 達也; 三好 誠司; 岡田 真人
日本物理学会講演概要集, 25 Aug. 2008, Not refereed, Not invited

21pWB-1 擬似教師つき学習とアンサンブル学習(ニューラルネットワーク,領域11,統計力学,物性基礎論,応用数学,力学,流体物理)
岡田 真人; 原 一之; 三好 誠司
日本物理学会講演概要集, 28 Feb. 2007, Not refereed, Not invited

21aWA-5 エージェント数が任意な場合の相互学習(情報統計力学,領域11,統計力学,物性基礎論,応用数学,力学,流体物理)
原 一之; 岡田 真人
日本物理学会講演概要集, 28 Feb. 2007, Not refereed, Not invited

アンサンブル学習の統合機構と相互学習
原 一之; 岡田 真人
電子情報通信学会技術研究報告. NC, ニューロコンピューティング, 09 Mar. 2006, Not refereed, Not invited

29pXH-14 潜在的な教師のある相互学習の統計力学(29pXH ニューラルネットワーク(神経系のモデルを含む),領域11(統計力学,物性基礎論,応用数学,力学,流体物理))
原 一之; 岡田 真人
日本物理学会講演概要集, 04 Mar. 2006, Not refereed, Not invited

潜在的な教師のある相互学習の統計力学
原 一之; 岡田 真人
電子情報通信学会技術研究報告. NC, ニューロコンピューティング, 16 Jun. 2005, Not refereed, Not invited

教師が非単調な場合のアンサンブル学習
三好 誠司; 原 一之; 岡田 真人
電子情報通信学会技術研究報告. NC, ニューロコンピューティング, 23 Mar. 2005, Not refereed, Not invited

24aYB-6 教師が非単調な場合のアンサンブル学習(情報統計力学・ニューラルネットワーク,領域11(統計力学,物性基礎論,応用数学,力学,流体物理))
三好 誠司; 原 一之; 岡田 真人
日本物理学会講演概要集, 04 Mar. 2005, Not refereed, Not invited

線形ウィークラーナーによるアンサンブル学習の汎化誤差の解析
原 一之; 岡田 真人
システム制御情報学会論文誌, 15 Dec. 2004, Not refereed, Not invited

14pTD-4 教師がコミティマシンの場合のアンサンブル学習(情報統計力学, 領域 11)
三好 誠司; 原 一之; 岡田 真人
日本物理学会講演概要集, 25 Aug. 2004, Not refereed, Not invited

14pTD-5 学習過程のノイズがパラレルブースティングに与える影響(情報統計力学, 領域 11)
原 一之; 岡田 真人
日本物理学会講演概要集, 25 Aug. 2004, Not refereed, Not invited

オンライン学習理論に基づく単純パーセプトロンのアンサンブル学習の解析(パターン認識)
三好 誠司; 原 一之; 岡田 真人
電子情報通信学会論文誌. D-II, 情報・システム, II-パターン処理, 01 Jul. 2004, Not refereed, Not invited

21pTQ-1 オンライン学習理論に基づく非線形単純パーセプトロンのアンサンブル学習の解析
三好 誠司; 原 一之; 岡田 真人
日本物理学会講演概要集, 15 Aug. 2003, Not refereed, Not invited

[チュートリアル講演]アンサンブル学習(<特集>統計的学習理論及び一般)
岡田 真人; 原 一之; 三好 誠司
電子情報通信学会技術研究報告. NC, ニューロコンピューティング, 22 Jul. 2003, Not refereed, Not invited

オンライン学習理論に基づく単純パーセプトロンのアンサンブル学習の解析(<特集>統計的学習理論及び一般)
三好 誠司; 原 一之; 岡田 真人
電子情報通信学会技術研究報告. NC, ニューロコンピューティング, 22 Jul. 2003, Not refereed, Not invited

パラレルブースティングのオンラインラーニングの理論
原 一之; 岡田 真人
電子情報通信学会技術研究報告. NC, ニューロコンピューティング, 20 Jun. 2003, Not refereed, Not invited

28aWJ-10 パラレルブースティングのオンラインラーニングの理論
原 一之; 岡田 真人
日本物理学会講演概要集, 06 Mar. 2003, Not refereed, Not invited

学習の問題を統計力学で取り扱う:線形パーセプトロンのアンサンブル学習を一例として (特集 情報論的学習理論--機械学習のさまざまな形)
岡田 真人; 原 一之
Computer today, Mar. 2003, Not refereed, Not invited

On-Line Learning of a Simple Perceptron Learning with Margin
Kazuyuki Hara; Masato Okada
電子情報通信学会論文誌. D-II, 情報・システム, II-パターン処理, 01 Oct. 2002, Refereed, Not invited
Lead

マージンを用いた単純パーセプトロン学習法のオンラインラーニングの理論
原 一之; 岡田 真人
電子情報通信学会技術研究報告. NC, ニューロコンピューティング, 14 Dec. 2001, Not refereed, Not invited

Performance of pre-learned convolution neural networks applied to recognition of overlapping digits
Dig SHII; Ryosuke MIYOSHI; and Kazuyuki Hara
2020 IEEE International Conference on Big Data and Smart Computing (BigComp), Feb. 2020, Korean Institute of Information Scientists and Engineers

Empirical Study of Effect of Dropout in Online Learning
Kazuyuki Hara
26th International Conference on Artificial Neural Networks, Sep. 2017, Europian Neural Network Society, Not invited

Analysis of Dropout Learning Regarded as Ensemble Learning
Kazuyuki Hara; Daisuke SAITOH; and Hayaru SHOUNO
25th international conference on artificial neural networks, Sep. 2016, European Neural Network Society, Not invited

Node-perturbation Learning for Soft-committee machine
Kazuyuki Hara
電子情報通信学会ニューラルコンピューティング研究会, Jan. 2016, 電子情報通信学会ニューラルコンピューティング研究会, Not invited

Proposal of novel dropout method and its analysis of dynamic property
Daisuke Saitoh
電子情報通信学会 ニューラルコンピューティング研究会, Jan. 2016, 電子情報通信学会 ニューラルコンピューティング研究会, Not invited

Dropout as an ensemble learning
Kazuyuki Hara
International Meeting on "High-dimensional Data Driven Science, Dec. 2015, Initiative for High-Dimensional Data-Driven Science through Deepening of Space Modeling, Not invited

The dropout accelerate symmetry breaking ?
Daisuke Saitoh; Kazuyuki hada
第25回 日本神経回路学会 全国大会, Sep. 2015, 日本神経回路学会, Not invited

Empirical study of model compression using true model
Tasuku Kondo; Hideitsu Hino; and Kazuyuki Hara
第25回 日本神経回路学会 全国大会, Sep. 2015, 日本神経回路学会, Not invited

Analysis of Function of Rectified Linear Unit Used in Deep learning
Kazuyuki Hara; Daisuke Saitoh; and Hayaru Shouno
The International Joint Conference on Neural Networks, Jul. 2015, International Neural Network Society, IEEE Computational Intelligence Society, Not invited

Mutual Learning Using Nonlinear Perceptron
Daisuke Saitoh; Kazuyuki Hara
Joint 7th International Conference on Soft Computing and Intelligent Systems and 15th International Symposium on Advanced Intelligent Systems, Dec. 2014, Japan Society for Fuzzy Theory and Intelligence Informatics, Not invited

Improving the Convergence Property of Soft Committee Machines by Replacing Derivative with Truncated Gaussian Function
Kazuyuki Hara
The 24th International Conference on Artificial Neural Networks, Sep. 2014, The European Neural Network Society, Not invited

Improving the Convergence Property of SoftCommittee Machines by Replacing Derivative with Truncated Gaussian Function
Kazuyuki Hara
The 24th International Conference on Artificial Neural Networks, Sep. 2014, The European Neural Network Society, Not invited

Soft Committee Machine Using Simple Derivative Term
Kazuyuki Hara
The 13th International Conference on Artificial Intelligence and Soft computing, Jun. 2014, Polish Neural Network Society, Not invited

Apr. 2000 - Present
The Physical Society of Japan

Apr. 1986 - Present
Institute of Electronics, Information and Communication Engineers

Classification problem adapt to environment, We want to attach classification problems whos data are given in on-line manner and characteristic of data will changed., We are studying on-line learning theory and have explored several algorithms. However, we want to apply our methods to real world problems to examine to show how our methods solve these problems, and how we must improve our methods.

深層学習によるCOVID-19感染伝搬と経済活動を同時制御する社会運営戦略の発見
日本学術振興会, 科学研究費補助金 基盤研究(C), Apr. 2021 - Mar. 2025
豊谷純、大前佑斗、原一之、高橋弘毅

オンライン学習におけるドロップアウトの理論と最適化に関する研究
独立行政法人日本学術振興会, 科学研究費補助金 基盤（C), Apr. 2018 - Mar. 2023
原 一之

Study on cooperation mechanism and it's dynamic behavior of many learning machines
Japan Society for the Promotion of Science, Grants-in-Aid for Scientific Research, 2004 - 2006
HARA Kazuyuki; MIYOSHI Seiji

IMPROVEMENT OF CONVERGENCE OF LEARNING OF MULTI-LAYER NEURAL NETWORKS AND APPLICATION FOR SEARCH ENGINE
Japan Society for the Promotion of Science, Grants-in-Aid for Scientific Research, 2001 - 2002
HARA Kazuyuki; NAKAYAMA Kenji