Neural architecture search (NAS) has attracted increasing attention. In recent years,
individual search methods have been replaced by weight-sharing search methods for higher …

Bi-Level Optimization (BLO) is originated from the area of economic game theory and then
introduced into the optimization community. BLO is able to handle problems with a …

Face anti-spoofing (FAS) plays a vital role in securing face recognition systems. Existing
methods heavily rely on the expert-designed networks, which may lead to a sub-optimal …

Class prototype construction and matching are core aspects of few-shot action recognition.
Previous methods mainly focus on designing spatiotemporal relation modeling modules or …

Few-shot fine-grained image classification (FSFGIC) methods refer to the classification of
images (eg, birds, flowers, and airplanes) belonging to different subclasses of the same …

Zero-shot learning (ZSL) aims to transfer knowledge from seen classes to semantically
related unseen classes, which are absent during training. The promising strategies for ZSL …

Variational quantum algorithms (VQAs) have been successfully applied to quantum
approximate optimization algorithms, variational quantum compiling and quantum machine …

Abstract Neural Architecture Search (NAS) is well-known for automatizing neural
architecture design and finding better architectures. Although NAS methods have shown …

Recent advances in neural architecture search inspire many channel number search
algorithms~(CNS) for convolutional neural networks. To improve searching efficiency …

Meta learning has attracted much attention recently in machine learning community.
Contrary to conventional machine learning aiming to learn inherent prediction rules to …