3 citations · 4 across the 2 of their papers we have counts for
3 papers
Accelerating Training using Tensor Decomposition
Mostafa Elhoushi, Ye Henry Tian, Zihao Chen +2
Tensor decomposition is one of the well-known approaches to reduce the latency time and number of parameters of a pre-trained model. However, in this paper, we propose an approach…
DeepShift: Towards Multiplication-Less Neural Networks
Mostafa Elhoushi, Zihao Chen, Farhan Shafiq +2
The high computation, memory, and power budgets of inferring convolutional neural networks (CNNs) are major bottlenecks of model deployment to edge computing platforms, e.g., mobil…
Automated flow for compressing convolution neural networks for efficient edge-computation with FPGA
Farhan Shafiq, Takato Yamada, Antonio T. Vilchez +1
Deep convolutional neural networks (CNN) based solutions are the current state- of-the-art for computer vision tasks. Due to the large size of these models, they are typically run…