26 citations · 33 across the 3 of their papers we have counts for
3 papers
cs.LG2019★ 7 cited
Accelerating Minibatch Stochastic Gradient Descent using Typicality Sampling
Xinyu Peng, Li Li, Fei-Yue Wang
Machine learning, especially deep neural networks, has been rapidly developed in fields including computer vision, speech recognition and reinforcement learning. Although Mini-batc…
cs.CR2016
A Fast Pseudo-Stochastic Sequential Cipher Generator Based on RBMs
Fei Hu, Xiaofei Xu, Tao Peng +2
Based on Restricted Boltzmann Machines (RBMs), an improved pseudo-stochastic sequential cipher generator is proposed. It is effective and efficient because of the two advantages: t…
cs.CV2016★ 26 cited
An image compression and encryption scheme based on deep learning
Fei Hu, Changjiu Pu, Haowei Gao +2
Stacked Auto-Encoder (SAE) is a kind of deep learning algorithm for unsupervised learning. Which has multi layers that project the vector representation of input data into a lower…