Adiabatic Quantum-Flux-Parametron (AQFP) is a superconducting logic with...
While vision transformers (ViTs) have continuously achieved new mileston...
Obstacle detection is a safety-critical problem in robot navigation, whe...
Recently, high-quality video conferencing with fewer transmission bits h...
Neural network quantization is a promising compression technique to redu...
Recent research demonstrated the promise of using resistive random acces...
Recent works demonstrated the promise of using resistive random access m...
Pretrained large-scale language models have increasingly demonstrated hi...
Mobile devices are becoming an important carrier for deep learning tasks...
To facilitate the deployment of deep neural networks (DNNs) on
resource-...
Recurrent neural networks (RNNs) based automatic speech recognition has
...
Structured weight pruning is a representative model compression techniqu...
Accelerating DNN execution on various resource-limited computing platfor...
The computing wall and data movement challenges of deep neural networks
...
Large deep neural network (DNN) models pose the key challenge to energy
...
The state-of-art DNN structures involve high computation and great deman...
Weight pruning and weight quantization are two important categories of D...