2017年10月7日 (六) 10:48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9月23日

陈 震： [x] Jeff. Dean et al., Large scale distributed deep networks. In Advances in neural information processing systems, pp. 1223-1231, 2012.

• 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)