「DeepLearning」深度学习基础

「DeepLearning」深度学习基础

灵魂书籍


[0] 深度学习圣经 ★★★★★

Bengio, Yoshua, Ian J. Goodfellow, and Aaron Courville. “Deep learning.” An MIT Press book. (2015).

https://github.com/HFTrader/DeepLearningBook/raw/master/DeepLearningBook.pdf

报告


[1] 三巨头报告★★★★★

LeCun, Yann, Yoshua Bengio, and Geoffrey Hinton. “Deep learning.” Nature 521.7553 (2015): 436-444.

http://www.cs.toronto.edu/%7Ehinton/absps/NatureDeepReview.pdf

深度信念网络 (DBN)


[1] 深度学习前夜的里程碑 ★★★

Hinton, Geoffrey E., Simon Osindero, and Yee-Whye Teh. “A fast learning algorithm for deep belief nets.” Neural computation 18.7 (2006): 1527-1554.

http://www.cs.toronto.edu/%7Ehinton/absps/ncfast.pdf

[2] 展示深度学习前景的里程碑 ★★★

Hinton, Geoffrey E., and Ruslan R. Salakhutdinov. “Reducing the dimensionality of data with neural networks.” Science 313.5786 (2006): 504-507.

http://www.cs.toronto.edu/%7Ehinton/science.pdf

ImageNet革命(深度学习大爆炸)


[1] AlexNet的深度学习突破 ★★★

Krizhevsky, Alex, Ilya Sutskever, and Geoffrey E. Hinton. “Imagenet classification with deep convolutional neural networks.” Advances in neural information processing systems. 2012.

http://papers.nips.cc/paper/4824-imagenet-classification-with-deep-convolutional-neural-networks.pdf

[2] VGGNet深度神经网络出现 ★★★

Simonyan, Karen, and Andrew Zisserman. “Very deep convolutional networks for large-scale image recognition.” arXiv preprint arXiv:1409.1556 (2014).

https://arxiv.org/pdf/1409.1556.pdf

[3] GoogLeNet ★★★

Szegedy, Christian, et al. “Going deeper with convolutions.” Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition. 2015.

http://www.cv-foundation.org/openaccess/content_cvpr_2015/papers/Szegedy_Going_Deeper_With_2015_CVPR_paper.pdf

[4] ResNet极深度神经网络,CVPR最佳论文 ★★★★★

He, Kaiming, et al. “Deep residual learning for image recognition.” arXiv preprintarXiv:1512.03385 (2015).

https://arxiv.org/pdf/1512.03385.pdf

语音识别革命


[1] 语音识别突破 ★★★★

Hinton, Geoffrey, et al. “Deep neural networks for acoustic modeling in speech recognition: The shared views of four research groups.” IEEE Signal Processing Magazine 29.6 (2012): 82-97.

http://cs224d.stanford.edu/papers/maas_paper.pdf

[2] RNN论文 ★★★

Graves, Alex, Abdel-rahman Mohamed, and Geoffrey Hinton. “Speech recognition with deep recurrent neural networks.” 2013 IEEE international conference on acoustics, speech and signal processing. IEEE, 2013.

http://arxiv.org/pdf/1303.5778.pdf

[3] 端对端RNN语音识别 ★★★

Graves, Alex, and Navdeep Jaitly. “Towards End-To-End Speech Recognition with Recurrent Neural Networks.” ICML. Vol. 14. 2014.

http://www.jmlr.org/proceedings/papers/v32/graves14.pdf

[4] Google语音识别系统论文 ★★★

Sak, Haşim, et al. “Fast and accurate recurrent neural network acoustic models for speech recognition.” arXiv preprint arXiv:1507.06947 (2015).

http://arxiv.org/pdf/1507.06947

[5] 百度语音识别系统论文 ★★★★

Amodei, Dario, et al. “Deep speech 2: End-to-end speech recognition in english and mandarin.” arXiv preprint arXiv:1512.02595 (2015).

https://arxiv.org/pdf/1512.02595.pdf

[6] 来自微软的当下最先进的语音识别论文 ★★★★

W. Xiong, J. Droppo, X. Huang, F. Seide, M. Seltzer, A. Stolcke, D. Yu, G. Zweig “Achieving Human Parity in Conversational Speech Recognition.” arXiv preprint arXiv:1610.05256 (2016).

https://arxiv.org/pdf/1610.05256v1

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