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Author:

Derbeko Philip,Dolev Shlomi,Gudes Ehud

Publisher

Springer International Publishing

Reference20 articles.

1. Bengio, Y., Laufer, E., Alain, G., Yosinski, J.: Deep generative stochastic networks trainable by backprop. In: ICML (2014)

2. Bengio, Y., Yao, L., Alain, G., Vincent, P.: Generalized denoising auto-encoders as generative models. In: NIPS (2013)

3. Creswell, A., Bharath, A.A.: Denoising adversarial autoencoders. IEEE Trans. Neural Netw. Learn. Syst. (2018)

4. Lecture Notes in Computer Science;P Derbeko,2018

5. Derbeko, P., Dolev, S., Gudes, E., Ullman, J.D.: Efficient and private approximations of distributed databases calculations. In: 2017 IEEE International Conference on Big Data, BigData 2017, Boston, MA, USA, 11–14 December 2017, pp. 4487–4496 (2017)

Cited by 2 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Adaptive sparse ternary gradient compression for distributed DNN training in edge computing;CCF Transactions on High Performance Computing;2022-03-18

2. ASTC: An Adaptive Gradient Compression Scheme for Communication-Efficient Edge Computing;2021 IEEE 23rd Int Conf on High Performance Computing & Communications; 7th Int Conf on Data Science & Systems; 19th Int Conf on Smart City; 7th Int Conf on Dependability in Sensor, Cloud & Big Data Systems & Application (HPCC/DSS/SmartCity/DependSys);2021-12

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