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103 lines
3.2 KiB
BibTeX
103 lines
3.2 KiB
BibTeX
@article{rosenblatt1958perceptron,
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title={The perceptron: a probabilistic model for information storage and organization in the brain.},
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author={Rosenblatt, Frank},
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journal={Psychological Review},
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volume={65},
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number={6},
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pages={386},
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year={1958},
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publisher={American Psychological Association}
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}
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@article{lecun1989backpropagation,
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title={Backpropagation applied to handwritten zip code recognition},
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author={LeCun, Yann and Boser, Bernhard and Denker, John S and Henderson, Donnie and Howard, Richard E and Hubbard, Wayne and Jackel, Lawrence D},
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journal={Neural computation},
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volume={1},
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number={4},
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pages={541--551},
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year={1989},
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publisher={MIT Press}
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}
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@inproceedings{krizhevsky2012imagenet,
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title={Imagenet classification with deep convolutional neural networks},
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author={Krizhevsky, Alex and Sutskever, Ilya and Hinton, Geoffrey E},
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booktitle={Advances in Neural Information Processing Systems},
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pages={1097--1105},
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year={2012}
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}
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@inproceedings{he2016deep,
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title={{Deep Residual Learning for Image Recognition}},
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author={He, Kaiming and Zhang, Xiangyu and Ren, Shaoqing and Sun, Jian},
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booktitle={Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},
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year={2016}
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}
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@article{rumelhart1986learning,
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title={Learning representations by back-propagating errors},
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author={Rumelhart, David E and Hinton, Geoffrey E and Williams, Ronald J},
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journal={Nature},
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volume={323},
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number={6088},
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pages={533},
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year={1986},
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publisher={Nature Publishing Group}
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}
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@article{Hochreiter1997lstm,
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author = {Hochreiter, Sepp and Hochreiter, S and Schmidhuber, J{\"{u}}rgen and Schmidhuber, J},
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isbn = {08997667 (ISSN)},
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issn = {0899-7667},
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journal = {Neural Computation},
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number = {8},
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pages = {1735--80},
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pmid = {9377276},
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title = {{Long Short-Term Memory.}},
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volume = {9},
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year = {1997}
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}
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@inproceedings{vaswani2017attention,
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title={Attention is all you need},
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author={Vaswani, Ashish and Shazeer, Noam and Parmar, Niki and Uszkoreit, Jakob and Jones, Llion and Gomez, Aidan N and Kaiser, {\L}ukasz and Polosukhin, Illia},
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booktitle={Advances in Neural Information Processing Systems},
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pages={5998--6008},
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year={2017}
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}
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@article{lecun2015deep,
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title={Deep learning},
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author={LeCun, Yann and Bengio, Yoshua and Hinton, Geoffrey},
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journal={Nature},
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volume={521},
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number={7553},
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pages={436},
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year={2015},
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publisher={Nature Publishing Group}
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}
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@inproceedings{KingmaAdam2014,
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title = {{Adam}: A Method for Stochastic Optimization},
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author = {Kingma, Diederik and Ba, Jimmy},
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booktitle = {Proceedings of the International Conference on Learning Representations (ICLR)},
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year = {2014}
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}
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@techreport{tieleman2012rmsprop,
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title={Divide the gradient by a running average of its recent magnitude. COURSERA: Neural networks for machine learning},
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author={Tieleman, T and Hinton, G},
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year={2017},
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institution={Technical Report}
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}
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@article{duchi2011adagrad,
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title={Adaptive subgradient methods for online learning and stochastic optimization},
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author={Duchi, John and Hazan, Elad and Singer, Yoram},
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journal={Journal of Machine Learning Research (JMLR)},
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volume={12},
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number={Jul},
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pages={2121--2159},
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year={2011}
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} |