Exploration strategies in continuous action space are often heuristic du...
In this study, we introduce a methodology for automatically transforming...
Although the security of automatic speaker verification (ASV) is serious...
Adversarial attack approaches to speaker identification either need high...
Sampling is an essential part of raw point cloud data processing such as...
One of the major difficulties of reinforcement learning is learning from...
This work aims to tackle Model Inversion (MI) attack on Split Federated
...
Deep learning has an increasing impact to assist research, allowing, for...
AI-based methods have been widely applied to tourism demand forecasting....
Split learning is a promising privacy-preserving distributed learning sc...
For in-vehicle application,task type and vehicle state information, i.e....
Randomness can be device-independently certified from a set of experimen...
More and more scholars focus on mobile edge computing (MEC) technology,
...
Currently, deep neural networks (DNNs) have achieved a great success in
...
Compared to traditional distributed computing environments such as grids...
When developing smart home systems, developers integrate and compose sma...
Local field potentials (LFPs) sampled with extracellular electrodes are
...