Recently, Generative Diffusion Models (GDMs) have showcased their remark...
Recent research has highlighted the vulnerability of Deep Neural Network...
With more people publishing their personal data online, unauthorized dat...
Fair classification aims to stress the classification models to achieve ...
The existence of adversarial examples brings huge concern for people to ...
Situating at the core of Artificial Intelligence (AI), Machine Learning ...
As one of the most successful AI-powered applications, recommender syste...
Click-Through Rate (CTR) prediction plays a key role in online advertisi...
Federated learning is considered as an effective privacy-preserving lear...
The recently proposed CP language adopts Compositional Programming: a ne...
Deep Neural Network (DNN) are vulnerable to adversarial attacks. As a
co...
This paper addresses the problem of automatically detecting human skin i...
Incorporating knowledge graph as side information has become a new trend...
Graph Neural Networks (GNNs) have boosted the performance for many
graph...
Adversarial training has been empirically proven to be one of the most
e...
Large-scale pre-trained models (PTMs) such as BERT and GPT have recently...
Recent studies suggest that “memorization” is one important factor for
o...
Differential lambda-calculus was first introduced by Thomas Ehrhard and
...
Adversarial training algorithms have been proven to be reliable to impro...
Meta learning algorithms have been widely applied in many tasks for effi...
DeepRobust is a PyTorch adversarial learning library which aims to build...
Deep neural networks (DNNs) have achieved significant performance in var...
Jointly utilizing global and local features to improve model accuracy is...
Deep neural networks (DNN) have achieved unprecedented success in numero...
Modern bio-technologies have produced a vast amount of high-throughput d...