Backpropagation

Results: 468



#Item
41Informatics 1 Cognitive Science (2015–2016) School of Informatics, University of Edinburgh Mirella Lapata Quiz 2: Perceptrons and Multilayer Perceptrons 1. Which one of the following is the perceptron’s input functio

Informatics 1 Cognitive Science (2015–2016) School of Informatics, University of Edinburgh Mirella Lapata Quiz 2: Perceptrons and Multilayer Perceptrons 1. Which one of the following is the perceptron’s input functio

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Source URL: www.inf.ed.ac.uk

Language: English - Date: 2016-02-11 08:41:30
42Recurrent Neural Net Learning and Vanishing Gradient  International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems 6(2):107{116, 1998 Sepp Hochreiter Institut fur Informatik

Recurrent Neural Net Learning and Vanishing Gradient International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems 6(2):107{116, 1998 Sepp Hochreiter Institut fur Informatik

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Source URL: www.bioinf.jku.at

Language: English - Date: 2013-01-23 02:14:24
43SIMPLIFYING NEURAL NETS BY DISCOVERING FLAT MINIMA Sepp Hochreiter Jurgen Schmidhubery

SIMPLIFYING NEURAL NETS BY DISCOVERING FLAT MINIMA Sepp Hochreiter Jurgen Schmidhubery

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Source URL: www.bioinf.jku.at

Language: English - Date: 2011-08-11 02:59:44
44GUESSING CAN OUTPERFORM MANY LONG TIME LAG ALGORITHMS Technical Note IDSIAJurgen Schmidhuber IDSIA

GUESSING CAN OUTPERFORM MANY LONG TIME LAG ALGORITHMS Technical Note IDSIAJurgen Schmidhuber IDSIA

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Source URL: www.bioinf.jku.at

Language: English - Date: 2013-01-23 02:10:32
45LSTM CAN SOLVE HARD LONG TIME LAG PROBLEMS Sepp Hochreiter Fakultat fur Informatik Technische Universitat Munchen

LSTM CAN SOLVE HARD LONG TIME LAG PROBLEMS Sepp Hochreiter Fakultat fur Informatik Technische Universitat Munchen

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Source URL: www.bioinf.jku.at

Language: English - Date: 2013-01-23 02:12:00
46Informatics 1 CG – Tutorial 2 Week 3 The goal of this tutorial is to deepen your understanding of perceptrons in general as well as the backpropagation algorithm used for training multilayer perceptrons. You should mak

Informatics 1 CG – Tutorial 2 Week 3 The goal of this tutorial is to deepen your understanding of perceptrons in general as well as the backpropagation algorithm used for training multilayer perceptrons. You should mak

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Source URL: www.inf.ed.ac.uk

Language: English - Date: 2015-01-23 06:08:04
47A Taxonomy and Library for Visualizing Learned Features in Convolutional Neural Networks ¨ Felix Grun Technische Universit¨at M¨unchen, Germany

A Taxonomy and Library for Visualizing Learned Features in Convolutional Neural Networks ¨ Felix Grun Technische Universit¨at M¨unchen, Germany

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Source URL: campar.in.tum.de

Language: English - Date: 2016-06-23 05:02:01
48Learning	Deep	Convolutional	Neural	Networks	 for	Places2	Scene	Recognition WM	Team Li	Shen

Learning Deep Convolutional Neural Networks for Places2 Scene Recognition WM Team Li Shen

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Source URL: image-net.org

Language: English - Date: 2015-12-21 12:22:54
49CS 224d: Assignment #2 Sunday 8th May, 2016 Due date: 5/5 11:59 PM PST (You are allowed to use three (3) late days maximum for this assignment) This handout consists of several homework problems, as well as instructions

CS 224d: Assignment #2 Sunday 8th May, 2016 Due date: 5/5 11:59 PM PST (You are allowed to use three (3) late days maximum for this assignment) This handout consists of several homework problems, as well as instructions

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Source URL: cs224d.stanford.edu

Language: English - Date: 2016-05-14 14:03:09
50REVIEW  doi:nature14539 Deep learning Yann LeCun1,2, Yoshua Bengio3 & Geoffrey Hinton4,5

REVIEW doi:nature14539 Deep learning Yann LeCun1,2, Yoshua Bengio3 & Geoffrey Hinton4,5

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Source URL: www.cs.toronto.edu

Language: English - Date: 2015-08-10 12:54:32