Many empirical studies have demonstrated the performance benefits of
con...
We propose Class Based Thresholding (CBT) to reduce the computational co...
Deep learning models that perform well often have high computational cos...
We present federated momentum contrastive clustering (FedMCC), a learnin...
Power iteration is a fundamental algorithm in data analysis. It extracts...
We consider a family of vector dot products that can be implemented usin...
State-of-the-art neural networks with early exit mechanisms often need
c...
We consider quantizing an Ld-dimensional sample, which is obtained by
co...
Robust and computationally efficient anomaly detection in videos is a pr...
Conventional principal component analysis (PCA) finds a principal vector...
We consider a distributed edge computing scenario consisting of several
...
We consider multiple unmanned aerial vehicles (UAVs) serving a density o...
We consider ad-hoc networks consisting of n wireless nodes that are loca...
We introduce and investigate the opportunities of multi-antenna communic...
Optimal deployment of unmanned aerial vehicles (UAVs) as communication r...