'Deep neural networks' diaporamas de présentation

Russell, 2009

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Novel approach to the particle track reconstruction based on deep learning methods

XXVI Symposium on Nuclear Electronics and Computing - NEC'2015 Montenegro, Budva , Becici , 25-29 September, 2017. Novel approach to the particle track reconstruction based on deep learning methods. P.Goncharov , S.Mitsyn , G.Ososkov , LIT JINR, Dubna , Russia ososkov@jinr.ru

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Deep Learning and Mixed Integer Optimization

Deep Learning and Mixed Integer Optimization. Matteo Fischetti, University of Padova. Machine Learning. Example (MIPpers only!): Continuous 0-1 Knapack Problem with a fixed n. of items. Implementing the ? in the box. Implementing the ? in the box. Deep Neural Networks (DNNs).

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Online deep learning for pulsed-signal data stream forecasting

Online deep learning for pulsed-signal data stream forecasting. C. Bower, A. Anjum, O. Bagdasar , N. Antonopoulos & A. Liotta University of Derby, UK. Agenda. Offline supervised deep learning Online deep learning Pulsed-signal forecasting Evolving stochastic optimisation algorithm

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Predicting Signal Peptides using Deep Neural Networks

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NVIDIA CES 2016 Highlights

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Deep Learning

Deep Learning. Deep learning?. MLP-> NN-> Deep Learning Deep networks trained with backpropagation (without unsupervised pretraining ) perform worse than shallow networks Supervised/unsupervised Each layer. Advantage. Deep Architectures can be representationally efficient

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Neural Network Software Market

Global Neural Network Software research report by information by type (Data Mining & Archiving, Analytical Software, Optimization Software, Visualization Software), by Component (Neural Network Software, Services, Platform), by End User by Regional Forecast Till 2023

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