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A new constrained maximum margin approach to discriminative learning of Bayesian classifiers None

Ke GUO, Xia-bi LIU, Lun-hao GUO, Zong-jie LI, Zeng-min GENG

Frontiers of Information Technology & Electronic Engineering 2018, Volume 19, Issue 5, Pages 639-650 doi: 10.1631/FITEE.1700007

Abstract: We propose a novel discriminative learning approach for Bayesian pattern classification, called ‘constrainedThe learning problem is to maximize the margin under the constraint that each training pattern is classified

Keywords： Discriminative learning Statistical modeling Bayesian pattern classifiers Gaussian mixture models UCI

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Erratum to: Latent discriminative representation learning for speaker recognition Erratum

Duolin Huang, Qirong Mao, Zhongchen Ma, Zhishen Zheng, Sidheswar Routray, Elias-Nii-Noi Ocquaye,2211708034@stmail.ujs.edu.cn,mao_qr@ujs.edu.cn,zhongchen_ma@ujs.edu.cn,1209103822@qq.com,sidheswar69@gmail.com,eocquaye@ujs.edu.cn

Frontiers of Information Technology & Electronic Engineering 2021, Volume 22, Issue 6, Pages 914-914 doi: 10.1631/FITEE.19e0690

Abstract: Unfortunately the fifth author’s name was mis-spelt. It should be Sidheswar ROUTRAY.

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Asymmetric discriminative correlation filters for visual tracking

Shui-wang Li, Qian-bo Jiang, Qi-jun Zhao, Li Lu, Zi-liang Feng,lishuiwang0721@163.com,jqianbo@163.com,qjzhao@scu.edu.cn,luli@scu.edu.cn,fengziliang@scu.edu.cn

Frontiers of Information Technology & Electronic Engineering 2020, Volume 21, Issue 10, Pages 1413-1534 doi: 10.1631/FITEE.1900507

Abstract: Discriminative correlation filters (DCF) are efficient in and have advanced the field significantly.With this operator, we propose a tracker called the asymmetric discriminative correlation filter (ADCF

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Latent discriminative representation learning for speaker recognition Research Articles

Duolin Huang, Qirong Mao, Zhongchen Ma, Zhishen Zheng, Sidheswar Routryar, Elias-Nii-Noi Ocquaye,2211708034@stmail.ujs.edu.cn,mao_qr@ujs.edu.cn,zhongchen_ma@ujs.edu.cn,1209103822@qq.com,sidheswar69@gmail.com,eocquaye@ujs.edu.cn

Frontiers of Information Technology & Electronic Engineering 2021, Volume 22, Issue 5, Pages 615-766 doi: 10.1631/FITEE.1900690

Abstract: Extracting discriminative speaker-specific representations from speech signals and transforming themWe mean that the learned representations in this study are not only discriminative but also relevant.Moreover, a reconstruction constraint intended to learn a is introduced to make representation discriminative

Keywords：说话人识别；潜在可区分性表征学习；说话人嵌入查找表；线性映射矩阵

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MSWNet: A visual deep machine learning method adopting transfer learning based upon ResNet 50 for municipal

Frontiers of Environmental Science & Engineering 2023, Volume 17, Issue 6, doi: 10.1007/s11783-023-1677-1

Abstract:

● MSWNet was proposed to classify municipal solid waste.

Keywords： Municipal solid waste sorting Deep residual network Transfer learning Cyclic learning rate Visualization

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Spatial prediction of soil contamination based on machine learning: a review

Frontiers of Environmental Science & Engineering 2023, Volume 17, Issue 8, doi: 10.1007/s11783-023-1693-1

Abstract:

● A review of machine learning (ML) for spatial prediction of soil

Keywords： Soil contamination Machine learning Prediction Spatial distribution

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Elucidate long-term changes of ozone in Shanghai based on an integrated machine learning method

Frontiers of Environmental Science & Engineering 2023, Volume 17, Issue 11, doi: 10.1007/s11783-023-1738-5

Abstract:

● A novel integrated machine learning method to analyze O₃

Keywords： Ozone Integrated method Machine learning

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Machine learning in building energy management: A critical review and future directions

Frontiers of Engineering Management 2022, Volume 9, Issue 2, Pages 239-256 doi: 10.1007/s42524-021-0181-1

Abstract: Over the past two decades, machine learning (ML) has elicited increasing attention in building energy

Keywords： building energy management machine learning integrated framework knowledge evolution

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Using machine learning models to explore the solution space of large nonlinear systems underlying flowsheet

Frontiers of Chemical Science and Engineering 2022, Volume 16, Issue 2, Pages 183-197 doi: 10.1007/s11705-021-2073-7

Abstract: exploration of the design variable space for such scenarios, an adaptive sampling technique based on machine learning

Keywords： machine learning flowsheet simulations constraints exploration

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Machine learning for fault diagnosis of high-speed train traction systems: A review

Frontiers of Engineering Management doi: 10.1007/s42524-023-0256-2

Abstract: In recent years, machine learning has been widely used in various pattern recognition tasks and has demonstratedMachine learning has made considerably advancements in traction system fault diagnosis; however, a comprehensiveThis paper primarily aims to review the research and application of machine learning in the field ofThen, the research and application of machine learning in traction system fault diagnosis are comprehensivelydiagnosis under actual operating conditions are revealed, and the future research trends of machine learning

Keywords： high-speed train traction systems machine learning fault diagnosis

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Dynamic prediction of moving trajectory in pipe jacking: GRU-based deep learning framework

Frontiers of Structural and Civil Engineering Pages 994-1010 doi: 10.1007/s11709-023-0942-5

Abstract: Hence, a gated recurrent unit (GRU)-based deep learning framework is proposed herein to dynamically predictdecision support for moving trajectory control and serve as a foundation for the application of deep learning

Keywords： dynamic prediction moving trajectory pipe jacking GRU deep learning

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Machine learning modeling identifies hypertrophic cardiomyopathy subtypes with genetic signature

Frontiers of Medicine 2023, Volume 17, Issue 4, Pages 768-780 doi: 10.1007/s11684-023-0982-1

Abstract: illustrating the relationship between the phenotype and genotype of each HCM subtype by using machine learningMachine learning modeling based on personal whole-exome data identified 46 genes with mutation burden

Keywords： machine learning methods hypertrophic cardiomyopathy genetic risk

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A new automatic convolutional neural network based on deep reinforcement learning for fault diagnosis

Frontiers of Mechanical Engineering 2022, Volume 17, Issue 2, doi: 10.1007/s11465-022-0673-7

Abstract: CNN (ACNN) for fault diagnosis, which can automatically tune its three key hyper parameters, namely, learningFirst, a new deep reinforcement learning (DRL) is developed, and it constructs an agent aiming at controllingACNN is also compared with other published machine learning (ML) and deep learning (DL) methods.

Keywords： deep reinforcement learning hyper parameter optimization convolutional neural network fault diagnosis

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Automated synthesis of steady-state continuous processes using reinforcement learning

Frontiers of Chemical Science and Engineering 2022, Volume 16, Issue 2, Pages 288-302 doi: 10.1007/s11705-021-2055-9

Abstract: The present work demonstrates how reinforcement learning can be used for automated flowsheet synthesis

Keywords： automated process synthesis flowsheet synthesis artificial intelligence machine learning reinforcementlearning

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State-of-the-art applications of machine learning in the life cycle of solid waste management

Frontiers of Environmental Science & Engineering 2023, Volume 17, Issue 4, doi: 10.1007/s11783-023-1644-x

Abstract:

● State-of-the-art applications of machine learning (ML) in solid waste

Keywords： Machine learning (ML) Solid waste (SW) Bibliometrics SW management Energy utilization Life cycle

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Title Author Date Type Operation

A new constrained maximum margin approach to discriminative learning of Bayesian classifiers

Ke GUO, Xia-bi LIU, Lun-hao GUO, Zong-jie LI, Zeng-min GENG

Journal Article

Erratum to: Latent discriminative representation learning for speaker recognition

Journal Article

Asymmetric discriminative correlation filters for visual tracking

Shui-wang Li, Qian-bo Jiang, Qi-jun Zhao, Li Lu, Zi-liang Feng,lishuiwang0721@163.com,jqianbo@163.com,qjzhao@scu.edu.cn,luli@scu.edu.cn,fengziliang@scu.edu.cn

Journal Article

Latent discriminative representation learning for speaker recognition

Journal Article

MSWNet: A visual deep machine learning method adopting transfer learning based upon ResNet 50 for municipal

Journal Article

Spatial prediction of soil contamination based on machine learning: a review

Journal Article

Elucidate long-term changes of ozone in Shanghai based on an integrated machine learning method

Journal Article

Machine learning in building energy management: A critical review and future directions

Journal Article

Using machine learning models to explore the solution space of large nonlinear systems underlying flowsheet

Journal Article

Machine learning for fault diagnosis of high-speed train traction systems: A review

Journal Article

Dynamic prediction of moving trajectory in pipe jacking: GRU-based deep learning framework

Journal Article

Machine learning modeling identifies hypertrophic cardiomyopathy subtypes with genetic signature

Journal Article

A new automatic convolutional neural network based on deep reinforcement learning for fault diagnosis

Journal Article

Automated synthesis of steady-state continuous processes using reinforcement learning

Journal Article

State-of-the-art applications of machine learning in the life cycle of solid waste management

Journal Article

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