As graph data size increases, the vast latency and memory consumption du...
The second-order training methods can converge much faster than first-or...
To deploy deep learning algorithms on resource-limited scenarios, an eme...
The training phases of Deep neural network (DNN) consumes enormous proce...
Vision transformer (ViT) has achieved competitive accuracy on a variety ...
Accelerating the neural network inference by FPGA has emerged as a popul...
Resistive Random-Access-Memory (ReRAM) crossbar is a promising technique...
Neural approximate computing gains enormous energy-efficiency at the cos...
Neural network based approximate computing is a universal architecture
p...
The training phases of Deep neural network (DNN) consume enormous proces...