“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2行: | 第2行: | ||
*2017年10月14日 | *2017年10月14日 | ||
− | + | 贺子航: [x] E. Nurvitadhi et al., Accelerating Binarized Neural Networks: Comparison of FPGA, CPU, GPU, and ASIC, International Conference on Field-Programmable Technology (FPT), pp. 77-84, 2016. | |
*2017年10月7日 | *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. | [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. | [x] Annett Ungethüm et al., Overview on Hardware Optimizations for Database Engines, BTW 2017. | ||
第17行: | 第17行: | ||
[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: | |
[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. | ||
2017年10月7日 (六) 10:44的版本
2017年学术活动
- 2017年10月14日
贺子航: [x] E. Nurvitadhi et al., Accelerating Binarized Neural Networks: Comparison of FPGA, CPU, GPU, and ASIC, International Conference on Field-Programmable Technology (FPT), pp. 77-84, 2016.
- 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
XXXX
[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)