Who Cited It

Learning representations by back-propagating errors

1986 · Nature · 31,688 citations · 60 from inside this corpus

David E. Rumelhart, Geoffrey E. Hinton, Ronald J. Williams

No abstract in the source record.

Learning representations by back-propagating errors (1986)Learning representations by b…Parallel Distributed Processing (1986)Parallel Distributed Processi…Support-vector networks (1995)Support-vector networksSupport-Vector Networks (1995)Support-Vector NetworksGreedy function approximation: A gradient boosting machine. (2001)Greedy function approximation…Distributed Representations of Words and Phrases and their Compositionality (2013)Distributed Representations o…Sequence to Sequence Learning with Neural Networks (2014)Sequence to Sequence Learning…Understanding the difficulty of training deep feedforward neural networks (2010)Understanding the difficulty …Deep Neural Networks for Acoustic Modeling in Speech Recognition: The Shared Views of Fou… (2012)Deep Neural Networks for Acou…Training feedforward networks with the Marquardt algorithm (1994)Training feedforward networks…Improving neural networks by preventing co-adaptation of feature detectors (2012)Improving neural networks by …Multitask Learning (1997)Multitask LearningDeep Learning with Differential Privacy (2016)Deep Learning with Differenti…Extreme Learning Machine for Regression and Multiclass Classification (2011)Extreme Learning Machine for …ADADELTA: An Adaptive Learning Rate Method (2012)ADADELTA: An Adaptive Learnin…Distributed Representations of Sentences and Documents (2014)Distributed Representations o…Learning Deep Architectures for AI (2009)Learning Deep Architectures f…Deep Learning in Medical Image Analysis (2017)Deep Learning in Medical Imag…Deep Reinforcement Learning: A Brief Survey (2017)Deep Reinforcement Learning: …The Limitations of Deep Learning in Adversarial Settings (2016)The Limitations of Deep Learn…Local Computations with Probabilities on Graphical Structures and Their Application to Ex… (1988)Local Computations with Proba…On the difficulty of training Recurrent Neural Networks (2012)On the difficulty of training…Neural Networks and the Bias/Variance Dilemma (1992)Neural Networks and the Bias/…Deep Convolutional Neural Networks for Image Classification: A Comprehensive Review (2017)Deep Convolutional Neural Net…Sequence to Sequence Learning with Neural Networks (2014)Character-level Convolutional Networks for Text Classification (2015)Character-level Convolutional…Learning and Transferring Mid-level Image Representations Using Convolutional Neural Netw… (2014)Learning and Transferring Mid…Deep learning for healthcare: review, opportunities and challenges (2017)Deep learning for healthcare:…Context-Dependent Pre-Trained Deep Neural Networks for Large-Vocabulary Speech Recognition (2011)Context-Dependent Pre-Trained…Survey on deep learning with class imbalance (2019)Survey on deep learning with …A Practical Bayesian Framework for Backpropagation Networks (1992)A Practical Bayesian Framewor…Methods for interpreting and understanding deep neural networks (2017)Methods for interpreting and …Phoneme recognition using time-delay neural networks (1989)Catastrophic forgetting in connectionist networks (1999)Catastrophic forgetting in co…Theory of the backpropagation neural network (1989)Theory of the backpropagation…Automatic differentiation in machine learning: a survey (2017)Automatic differentiation in …Threat of Adversarial Attacks on Deep Learning in Computer Vision: A Survey (2018)Threat of Adversarial Attacks…
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What this paper cites, inside the corpus

PaperYearCited
Parallel Distributed Processing198615,411

What cites it, inside the corpus

PaperYearCited
Support-vector networks199541,028
Support-Vector Networks199533,914
Greedy function approximation: A gradient boosting machine.200130,137
Distributed Representations of Words and Phrases and their Compositionality201318,054
Sequence to Sequence Learning with Neural Networks201413,351
Understanding the difficulty of training deep feedforward neural networks201012,673
Deep Neural Networks for Acoustic Modeling in Speech Recognition: The Shared Views of Fou…201210,399
Training feedforward networks with the Marquardt algorithm19947,739
Improving neural networks by preventing co-adaptation of feature detectors20126,653
Multitask Learning19976,478
Deep Learning with Differential Privacy20166,220
Extreme Learning Machine for Regression and Multiclass Classification20115,581
ADADELTA: An Adaptive Learning Rate Method20125,532
Distributed Representations of Sentences and Documents20145,121
Learning Deep Architectures for AI20095,077
Deep Learning in Medical Image Analysis20174,917
Deep Reinforcement Learning: A Brief Survey20174,434
The Limitations of Deep Learning in Adversarial Settings20163,980
Local Computations with Probabilities on Graphical Structures and Their Application to Ex…19883,977
On the difficulty of training Recurrent Neural Networks20123,801
Neural Networks and the Bias/Variance Dilemma19923,612
Deep Convolutional Neural Networks for Image Classification: A Comprehensive Review20173,570
Sequence to Sequence Learning with Neural Networks20143,514
Character-level Convolutional Networks for Text Classification20153,280
Learning and Transferring Mid-level Image Representations Using Convolutional Neural Netw…20143,197
Deep learning for healthcare: review, opportunities and challenges20173,115
Context-Dependent Pre-Trained Deep Neural Networks for Large-Vocabulary Speech Recognition20113,089
Survey on deep learning with class imbalance20192,971
A Practical Bayesian Framework for Backpropagation Networks19922,962
Methods for interpreting and understanding deep neural networks20172,763
Phoneme recognition using time-delay neural networks19892,650
Catastrophic forgetting in connectionist networks19992,358
Theory of the backpropagation neural network19892,239
Automatic differentiation in machine learning: a survey20172,094
Threat of Adversarial Attacks on Deep Learning in Computer Vision: A Survey20182,090

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DOI · OpenAlex record

Topics

Neural Networks and ApplicationsComputer Science
Control Systems and IdentificationEngineering
Blind Source Separation TechniquesComputer Science

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complete

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  • supports3 author record(s) attached.
  • supports4 reference(s) recorded.
  • neutralThe DOI carries no year to check against.
  • supportsA title is present.

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