With the rapid advancements of deep learning in recent years, hardware
a...
Memory-aware network scheduling is becoming increasingly important for d...
Efficient networks, e.g., MobileNetV2, EfficientNet, etc, achieves
state...
Markov chain Monte Carlo (MCMC) is a widely used sampling method in mode...
We propose a data-driven and machine-learning-based approach to compute
...
Accurate early congestion prediction can prevent unpleasant surprises at...
While the performance of deep convolutional neural networks for image
su...
Secure multi-party computation (MPC) enables computation directly on
enc...
Signal processing in wireless communications, such as precoding, detecti...
The electronic design automation (EDA) community has been actively explo...
Multigrid methods are one of the most efficient techniques for solving l...
Deep generative models, since their inception, have become increasingly ...
The state-of-the-art deep learning algorithms rely on distributed traini...
In this paper, we propose a machine-learning assisted modeling framework...
Stochastic computing (SC) presents high error tolerance and low hardware...