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Page 1: yann.lecun.comyann.lecun.com/exdb/publis/pdf/becker-lecun-89.pdf · optimization methods towards improving the con- vergence of back-propagation. We then describe a computationally
Page 2: yann.lecun.comyann.lecun.com/exdb/publis/pdf/becker-lecun-89.pdf · optimization methods towards improving the con- vergence of back-propagation. We then describe a computationally
Page 3: yann.lecun.comyann.lecun.com/exdb/publis/pdf/becker-lecun-89.pdf · optimization methods towards improving the con- vergence of back-propagation. We then describe a computationally
Page 4: yann.lecun.comyann.lecun.com/exdb/publis/pdf/becker-lecun-89.pdf · optimization methods towards improving the con- vergence of back-propagation. We then describe a computationally
Page 5: yann.lecun.comyann.lecun.com/exdb/publis/pdf/becker-lecun-89.pdf · optimization methods towards improving the con- vergence of back-propagation. We then describe a computationally
Page 6: yann.lecun.comyann.lecun.com/exdb/publis/pdf/becker-lecun-89.pdf · optimization methods towards improving the con- vergence of back-propagation. We then describe a computationally
Page 7: yann.lecun.comyann.lecun.com/exdb/publis/pdf/becker-lecun-89.pdf · optimization methods towards improving the con- vergence of back-propagation. We then describe a computationally
Page 8: yann.lecun.comyann.lecun.com/exdb/publis/pdf/becker-lecun-89.pdf · optimization methods towards improving the con- vergence of back-propagation. We then describe a computationally
Page 9: yann.lecun.comyann.lecun.com/exdb/publis/pdf/becker-lecun-89.pdf · optimization methods towards improving the con- vergence of back-propagation. We then describe a computationally
Page 10: yann.lecun.comyann.lecun.com/exdb/publis/pdf/becker-lecun-89.pdf · optimization methods towards improving the con- vergence of back-propagation. We then describe a computationally

DEEP LEARNING - REVIEW - Pennsylvania State … · Deep Learning - History, Background & Applications. ... Source : Deep learning Yann LeCun, Yoshua Bengio, Geoffrey Hinton Nature

DEEP LEARNING - REVIEW - Pennsylvania State … · Deep Learning - History, Background & Applications. ... Source : Deep learning Yann LeCun, Yoshua Bengio, Geoffrey Hinton Nature

Tutorial: Learning Deep Architectures - University of …rsalakhu/deeplearning/yoshua_icml2009.pdf · Tutorial: Learning Deep Architectures Yoshua Bengio, U. Montreal Yann LeCun,

Tutorial: Learning Deep Architectures - University of …rsalakhu/deeplearning/yoshua_icml2009.pdf · Tutorial: Learning Deep Architectures Yoshua Bengio, U. Montreal Yann LeCun,

Transformation Invariance in Pattern Recognition - Yann LeCun

Transformation Invariance in Pattern Recognition - Yann LeCun

Large-ScaleFPGA-basedConvolutionalNetworksyann.lecun.com/exdb/publis/pdf/farabet-suml-11.pdfLarge-ScaleFPGA-basedConvolutionalNetworks Cl´ement Farabet1, Yann LeCun1, Koray Kavukcuoglu1,

Large-ScaleFPGA-basedConvolutionalNetworksyann.lecun.com/exdb/publis/pdf/farabet-suml-11.pdfLarge-ScaleFPGA-basedConvolutionalNetworks Cl´ement Farabet1, Yann LeCun1, Koray Kavukcuoglu1,

Y LeCun MA Ranzato - Computational Intelligence, Learning ... Sparse Coding Pooling ... Y LeCun MA Ranzato Deep Learning and Feature Learning Today ... Y LeCun MA Ranzato SHALLOW DEEP

Y LeCun MA Ranzato - Computational Intelligence, Learning ... Sparse Coding Pooling ... Y LeCun MA Ranzato Deep Learning and Feature Learning Today ... Y LeCun MA Ranzato SHALLOW DEEP

Learning Image FeaturesLearning Image Featuresyann/talks/lecun-20100710-pcmi-00...Yann LeCun Vision occupies a big chunk of our brainsVision occupies a big chunk of our brains 1/3

Learning Image FeaturesLearning Image Featuresyann/talks/lecun-20100710-pcmi-00...Yann LeCun Vision occupies a big chunk of our brainsVision occupies a big chunk of our brains 1/3

Optimization & Deep Learning 2017. 4. 19. · Z. Y LeCun Dynamic Factor Graphs Target Prop for Recurrent Nets Deep Learning for Time-Series Prediction – [Mirowski & LeCun ECML 09]

Optimization & Deep Learning 2017. 4. 19. · Z. Y LeCun Dynamic Factor Graphs Target Prop for Recurrent Nets Deep Learning for Time-Series Prediction – [Mirowski & LeCun ECML 09]

OverFeat: Integrated Recognition, Localization and Detection ...yann.lecun.com/exdb/publis/pdf/sermanet-iclr-14.pdfThis integrated framework is the winner of the localization task

OverFeat: Integrated Recognition, Localization and Detection ...yann.lecun.com/exdb/publis/pdf/sermanet-iclr-14.pdfThis integrated framework is the winner of the localization task

Neural Networks William Cohen 10-601 [pilfered from: Ziv; Geoff Hinton; Yoshua Bengio; Yann LeCun; Hongkak…

Neural Networks William Cohen 10-601 [pilfered from: Ziv; Geoff Hinton; Yoshua Bengio; Yann LeCun; Hongkak…

Y LeCun MA Ranzato 2014-04-13 · Y LeCun MA Ranzato This Basic Model has not evolved much since the 50's The first learning machine: the Perceptron Built at Cornell in 1960 The Perceptron

Y LeCun MA Ranzato 2014-04-13 · Y LeCun MA Ranzato This Basic Model has not evolved much since the 50's The first learning machine: the Perceptron Built at Cornell in 1960 The Perceptron

yann.lecun.comyann.lecun.com/exdb/publis/pdf/matic-94.pdf · The complete visitor sign-in procedure on the PENGUIN system consists of several steps: The visitor has to fill-in the

yann.lecun.comyann.lecun.com/exdb/publis/pdf/matic-94.pdf · The complete visitor sign-in procedure on the PENGUIN system consists of several steps: The visitor has to fill-in the

yann.lecun.comyann.lecun.com/exdb/publis/pdf/jackel-95.pdf · 12 0.50 0.96 0199 Figure 4. Blocks of segments from Figure 3 that are passed to LeNet. The number near the top of each

yann.lecun.comyann.lecun.com/exdb/publis/pdf/jackel-95.pdf · 12 0.50 0.96 0199 Figure 4. Blocks of segments from Figure 3 that are passed to LeNet. The number near the top of each

Yann LeCun’s important paperyann.lecun.com/exdb/publis/pdf/lecun-88.pdf ·  · 2004-12-20Among all the supervised learning algo- rithms, back propagation (BP) is proba- bly the

Yann LeCun’s important paperyann.lecun.com/exdb/publis/pdf/lecun-88.pdf ·  · 2004-12-20Among all the supervised learning algo- rithms, back propagation (BP) is proba- bly the

Scaling Learning Algorithms towards AI - Yann LeCunyann.lecun.com/exdb/publis/pdf/bengio-lecun-07.pdf · 2007-08-24 · Scaling Learning Algorithms towards AI Yoshua Bengio (1) and

Scaling Learning Algorithms towards AI - Yann LeCunyann.lecun.com/exdb/publis/pdf/bengio-lecun-07.pdf · 2007-08-24 · Scaling Learning Algorithms towards AI Yoshua Bengio (1) and

Automatic Recognition of Biological Particles in ...yann.lecun.com/exdb/publis/pdf/ranzato-07a.pdf · Automatic Recognition of Biological Particles ... from a mixture-of-Gaussians

Automatic Recognition of Biological Particles in ...yann.lecun.com/exdb/publis/pdf/ranzato-07a.pdf · Automatic Recognition of Biological Particles ... from a mixture-of-Gaussians

yann.lecun.comyann.lecun.com/exdb/publis/pdf/matan-90.pdf · Handwritten Character Recognition Using Neural Network ... networks in real-world ... knowledge of the probability of

yann.lecun.comyann.lecun.com/exdb/publis/pdf/matan-90.pdf · Handwritten Character Recognition Using Neural Network ... networks in real-world ... knowledge of the probability of

Neural Networks and Deep Learning Slides credit: Geoffrey Hinton and Yann LeCun.

Neural Networks and Deep Learning Slides credit: Geoffrey Hinton and Yann LeCun.

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ÑÔZ]; =IQYÐ 9QY=IQOÏdÛ]A ?69>Z[;CùyUY8 ...yann.lecun.com/exdb/publis/pdf/simard-00.pdf · s(® * ! " # ! # . $ .- "! # $#

Lecun 20060816-ciar-01-energy based learning

Lecun 20060816-ciar-01-energy based learning

Guía de puesta en servicio y de mantenimiento · 3 Guía de instalación y de mantenimiento - FLSD ZONA 1 – Exdb / Exdb eb 5699 es - 2020.02 / c Estimado cliente: Usted acaba de

Guía de puesta en servicio y de mantenimiento · 3 Guía de instalación y de mantenimiento - FLSD ZONA 1 – Exdb / Exdb eb 5699 es - 2020.02 / c Estimado cliente: Usted acaba de