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检索条件"主题词=pseudoinverse learning algorithm"
6 条 记 录,以下是1-10 订阅
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A pseudoinverse learning algorithm for feedforward neural networks with stacked generalization applications to software reliability growth data
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NEUROCOMPUTING 2004年 第1期56卷 101-121页
作者: Guo, P Lyu, MR Chinese Univ Hong Kong Dept Comp Sci & Engn Shatin Hong Kong Peoples R China Beijing Normal Univ Dept Comp Sci Beijing 100875 Peoples R China
A supervised learning algorithm, pseudoinverse learning algorithm (PIL), for feedforward neural networks is developed. The algorithm is based on generalized linear algebraic methods, and it adopts matrix inner product... 详细信息
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A Hierarchical Model with pseudoinverse learning algorithm Optimazation for Pulsar Candidate Selection
A Hierarchical Model with Pseudoinverse Learning Algorithm O...
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IEEE Congress on Evolutionary Computation (IEEE CEC) as part of the IEEE World Congress on Computational Intelligence (IEEE WCCI)
作者: Li, Shijia Feng, Sibo Guo, Ping Yin, Qian Beijing Normal Univ Image Proc & Pattern Recognit Lab Beijing 100875 Peoples R China
Pulsars search has always been one of the most concerned problem in the field of astronomy. Nowadays, with the development of astronomical instruments and observation technology, the amount of data is getting bigger a... 详细信息
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Broad and pseudoinverse learning for Autoencoder
Broad and Pseudoinverse Learning for Autoencoder
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IEEE International Conference on Systems, Man, and Cybernetics (SMC)
作者: Xu, Bingxin Guo, Ping Beijing Union Univ Beijing Key Lab Informat Serv Engn Beijing 100101 Peoples R China Beijing Normal Univ Sch Syst Sci Image Pro & Patt Recog Lab Beijing 100875 Peoples R China
Autoencoder is one approach to automatically learn features from unlabeled data and received significant attention during the development of deep neural networks. However, the learning algorithm of autoencoder suffers... 详细信息
来源: 评论
pseudoinverse learning Algorithom for Fast Sparse Autoencoder Training
Pseudoinverse Learning Algorithom for Fast Sparse Autoencode...
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IEEE Congress on Evolutionary Computation (IEEE CEC) as part of the IEEE World Congress on Computational Intelligence (IEEE WCCI)
作者: Xu, Bingxin Guo, Ping Beijing Union Univ Beijing Key Lab Informat Serv Engn Beijing 100101 Peoples R China Beijing Normal Univ Sch Syst Sci Image Proc & Pattern Recognit Lab Beijing 100875 Peoples R China
Sparse autoencoder is one approach to automatically learn features from unlabeled data and received significant attention during the development of deep neural networks. However, the learning algorithm of sparse autoe... 详细信息
来源: 评论
An efficient and effective deep convolutional kernel pseudoinverse learner with multi-filter
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NEUROCOMPUTING 2021年 457卷 74-83页
作者: Deng, Xiaodan Mahmoud, Mohammed A. B. Yin, Qian Guo, Ping Beijing Normal Univ Sch Syst Sci Image Proc & Pattern Recognit Lab Beijing 100875 Peoples R China Beijing Inst Technol Sch Comp Sci & Technol Beijing 100081 Peoples R China Beijing Normal Univ Sch Artificial Intelligence Image Proc & Pattern Recognit Lab Beijing 100875 Peoples R China
The convolutional neural network is the most widely used deep neural network. However, it still has some disadvantages. First, the back-propagation method is usually used in the training of convolutional neural networ... 详细信息
来源: 评论
pseudoinverse learning Algorithom for Fast Sparse Autoencoder Training
Pseudoinverse Learning Algorithom for Fast Sparse Autoencode...
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IEEE Congress on Evolutionary Computation
作者: Bingxin Xu Ping Guo Beijing Key Laboratory of Information Service Engineering Beijing Union University Beijing China Image Processing and Pattern Recognition Laboratory Beijing Normal University Beijing 100875 China
Sparse autoencoder is one approach to automatically learn features from unlabeled data and received significant attention during the development of deep neural networks. However, the learning algorithm of sparse autoe... 详细信息
来源: 评论