“Student-Research-Training-THU”版本间的差异
（→2017年学术活动） |
（→2017年学术活动） |
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| 第4行： | 第4行： | ||
柳荫： | 柳荫： | ||
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[x] Huang, Gao, Zhuang Liu, Kilian Q. Weinberger, and Laurens van der Maaten, Densely Connected Convolutional Networks, CVPR 2017. | [x] Huang, Gao, Zhuang Liu, Kilian Q. Weinberger, and Laurens van der Maaten, Densely Connected Convolutional Networks, CVPR 2017. | ||
陈震： | 陈震： | ||
| − | |||
[x] Annett Ungethüm et al., Overview on Hardware Optimizations for Database Engines, BTW 2017. | [x] Annett Ungethüm et al., Overview on Hardware Optimizations for Database Engines, BTW 2017. | ||
| 第14行： | 第12行： | ||
郑文勋： | 郑文勋： | ||
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[x] Graves, A., Wayne, G. and Danihelka, I., 2014. Neural turing machines. arXiv preprint arXiv:1410.5401. | [x] Graves, A., Wayne, G. and Danihelka, I., 2014. Neural turing machines. arXiv preprint arXiv:1410.5401. | ||
陈震： | 陈震： | ||
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[x] Jouppi, N.P. et al., In-Datacenter Performance Analysis of a Tensor Processing Unit, ISCA 2017. | [x] Jouppi, N.P. et al., In-Datacenter Performance Analysis of a Tensor Processing Unit, ISCA 2017. | ||
| 第24行： | 第20行： | ||
郑文勋： | 郑文勋： | ||
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[x] Yu Su et al., In-Situ Bitmaps Generation and Efficient Data Analysis based on Bitmaps, HPDC 2015. | [x] Yu Su et al., In-Situ Bitmaps Generation and Efficient Data Analysis based on Bitmaps, HPDC 2015. | ||
| 第30行： | 第25行： | ||
郑文勋： | 郑文勋： | ||
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[x] Nguyen, Anh, Jason Yosinski, and Jeff Clune. "Deep neural networks are easily fooled: High confidence predictions for unrecognizable images." CVPR. 2015. | [x] Nguyen, Anh, Jason Yosinski, and Jeff Clune. "Deep neural networks are easily fooled: High confidence predictions for unrecognizable images." CVPR. 2015. | ||
2017年10月7日 (六) 08:15的版本
2017年学术活动
- 2017年10月7日
柳荫： [x] Huang, Gao, Zhuang Liu, Kilian Q. Weinberger, and Laurens van der Maaten, Densely Connected Convolutional Networks, CVPR 2017.
陈震： [x] Annett Ungethüm et al., Overview on Hardware Optimizations for Database Engines, BTW 2017.
- 2017年9月30日
郑文勋： [x] Graves, A., Wayne, G. and Danihelka, I., 2014. Neural turing machines. arXiv preprint arXiv:1410.5401.
陈震： [x] Jouppi, N.P. et al., In-Datacenter Performance Analysis of a Tensor Processing Unit, ISCA 2017.
- 2017年5月21日
郑文勋： [x] Yu Su et al., In-Situ Bitmaps Generation and Efficient Data Analysis based on Bitmaps, HPDC 2015.
- 2017年4月8日
郑文勋： [x] Nguyen, Anh, Jason Yosinski, and Jeff Clune. "Deep neural networks are easily fooled: High confidence predictions for unrecognizable images." CVPR. 2015.
供选论文清单
TensorFlow系列
DistBelief - large deep networks, nips 2012.
TensorFlow: A system for large-scale machine learning, OSDI 2016.
TPU - In-Datacenter Performance Analysis of a Tensor Processing Unit, ISCA 2017.
CV系列
Densely Connected Convolutional Networks,CVPR 2017.
ASR语音识别
Multichannel Signal Processing with Deep Neural Networks for Automatic Speech Recognition-TASLP-2017
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[Quasi-Recurrent Neural Networks](https://arxiv.org/abs/1611.01576)
[Training RNNs as Fast as CNNs](https://arxiv.org/abs/1709.02755)
[Semi-Supervised Classification with Graph Convolutional Networks](https://arxiv.org/abs/1609.02907)
[A Survey on Transfer Learning](http://www3.ntu.edu.sg/home/sinnopan/publications/TLsurvey_0822.pdf)
[How transferable are features in deep neuralnetworks?](https://arxiv.org/abs/1411.1792)
[Progressive Neural Networks](https://arxiv.org/abs/1606.04671)
[One-Shot Learning of Object Categories](http://vision.stanford.edu/documents/Fei-FeiFergusPerona2006.pdf)
[One-shot Learning with Memory-Augmented Neural Networks](https://arxiv.org/abs/1605.06065)
[Auto-Encoding Variational Bayes](https://arxiv.org/abs/1312.6114)
[Autoencoding beyond pixels using a learned similarity metric](https://arxiv.org/abs/1512.09300)
