Zobrazeno 1 - 10
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pro vyhledávání: '"Allred, Jason"'
Autor:
Allred, Jason, Roy, Kaushik
Spiking Neural Networks (SNNs) are being explored for their potential energy efficiency benefits due to sparse, event-driven computation. Non-spiking artificial neural networks are typically trained with stochastic gradient descent using backpropagat
Externí odkaz:
http://arxiv.org/abs/2111.09446
Spiking Neural Networks (SNNs) are being explored for their potential energy efficiency resulting from sparse, event-driven computations. Many recent works have demonstrated effective backpropagation for deep Spiking Neural Networks (SNNs) by approxi
Externí odkaz:
http://arxiv.org/abs/2003.01250
Autor:
Allred, Jason M., Roy, Kaushik
Stochastic gradient descent requires that training samples be drawn from a uniformly random distribution of the data. For a deployed system that must learn online from an uncontrolled and unknown environment, the ordering of input samples often fails
Externí odkaz:
http://arxiv.org/abs/1902.03187
Autor:
Zhang, Zhen, Mondal, Sandip, Mandal, Subhasish, Allred, Jason M., Aghamiri, Neda Alsadat, Fali, Alireza, Zhang, Zhan, Zhou, Hua, Cao, Hui, Rodolakis, Fanny, McChesney, Jessica L., Wang, Qi, Sun, Yifei, Abate, Yohannes, Roy, Kaushik, Rabe, Karin M., Ramanathan, Shriram
Publikováno v:
Proceedings of the National Academy of Sciences of the United States of America, 2021 Sep . 118(39), 1-7.
Externí odkaz:
https://www.jstor.org/stable/27075809
Publikováno v:
IEEE Journal on Emerging and Selected Topics in Circuits and Systems (Volume: 8, Issue: 1, March 2018)
A fundamental feature of learning in animals is the "ability to forget" that allows an organism to perceive, model and make decisions from disparate streams of information and adapt to changing environments. Against this backdrop, we present a novel
Externí odkaz:
http://arxiv.org/abs/1703.07655
Autor:
Allred, Jason M
Computing with Artificial Neural Networks (ANNs) is a branch of machine learning that has seen substantial growth over the last decade, significantly increasing the accuracy and capability of machine learning systems. ANNs are connected networks of c
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::31a379eddf43824526b26dd0c8bab50a
Akademický článek
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Autor:
Zhen Zhang, Mondal, Sandip, Mandal, Subhasish, Allred, Jason M., Aghamiri, Neda Alsadat, Fali, Alireza, Zhan Zhang, Hua Zhou, Hui Cao, Rodolakis, Fanny, McChesney, Jessica L., Qi Wang, Yifei Sun, Abate, Yohannes, Roy, Kaushik, Rabe, Karin M., Ramanathan, Shriram
Publikováno v:
Proceedings of the National Academy of Sciences of the United States of America; 9/28/2021, Vol. 118 Issue 39, p1-7, 7p