Titlebook: Artificial Neural Networks and Machine Learning – ICANN 2019: Theoretical Neural Computation; 28th International C Igor V. Tetko,Věra Kůrko

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书目名称Artificial Neural Networks and Machine Learning – ICANN 2019: Theoretical Neural Computation影响因子(影响力)




书目名称Artificial Neural Networks and Machine Learning – ICANN 2019: Theoretical Neural Computation影响因子(影响力)学科排名




书目名称Artificial Neural Networks and Machine Learning – ICANN 2019: Theoretical Neural Computation网络公开度




书目名称Artificial Neural Networks and Machine Learning – ICANN 2019: Theoretical Neural Computation网络公开度学科排名




书目名称Artificial Neural Networks and Machine Learning – ICANN 2019: Theoretical Neural Computation被引频次




书目名称Artificial Neural Networks and Machine Learning – ICANN 2019: Theoretical Neural Computation被引频次学科排名




书目名称Artificial Neural Networks and Machine Learning – ICANN 2019: Theoretical Neural Computation年度引用




书目名称Artificial Neural Networks and Machine Learning – ICANN 2019: Theoretical Neural Computation年度引用学科排名




书目名称Artificial Neural Networks and Machine Learning – ICANN 2019: Theoretical Neural Computation读者反馈




书目名称Artificial Neural Networks and Machine Learning – ICANN 2019: Theoretical Neural Computation读者反馈学科排名

gentle

Norifumi Fujimura,Takeshi Yoshimurade video game and implement a local plasticity rule that enables reinforcement learning, allowing the on-chip neural network to learn to play the game. The experiment demonstrates key aspects of the employed approach, such as accelerated and flexible learning, high energy efficiency and resilience to noise.

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Chemotherapy

Brain-Inspired Hardware for Artificial Intelligence: Accelerated Learning in a Physical-Model Spikinde video game and implement a local plasticity rule that enables reinforcement learning, allowing the on-chip neural network to learn to play the game. The experiment demonstrates key aspects of the employed approach, such as accelerated and flexible learning, high energy efficiency and resilience to noise.

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0302-9743 ngs was carefully reviewed and selected from 494 submissions. They were organized in 5 volumes focusing on theoretical neural computation; deep learning; image processing; text and time series; and workshop and special sessions. .978-3-030-30486-7978-3-030-30487-4Series ISSN 0302-9743 Series E-ISSN 1611-3349

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Sleep State Analysis Using Calcium Imaging Data by Non-negative Matrix Factorizationties in time from calcium imaging data. NMF was used because neural activity can be expressed by the sum of individual neuronal activity and fluorescence intensity data are always positive values. We found that there are certain groups of neurons that behave differently between sleep and wake states.