Partial label learning (PLL) is an emerging framework in weakly supervised machine
learning with broad application prospects. It handles the case in which each training …

Recommender Systems (RSs), which generate personalized content, have become a
technological tool with diverse applications for users. While numerous RSs have been …

Specific emitter identification (SEI) plays an increasingly crucial and potential role in both
military and civilian scenarios. It refers to a process to discriminate individual emitters from …

In an effort to further advance semi-supervised generative and classification tasks, we
propose a simple yet effective training strategy called* dual pseudo training*(DPT), built …

Continual learning usually assumes the incoming data are fully labeled, which might not be
applicable in real applications. In this work, we consider semi-supervised continual learning …

The profound impact of deep learning and particularly of convolutional neural networks
(CNNs) in automatic image processing has been decisive for the progress and evolution of …

The survival analysis on histological whole-slide images (WSIs) is one of the most important
means to estimate patient prognosis. Although many weakly-supervised deep learning …

Retinopathy is the primary cause of irreversible yet preventable blindness. Numerous deep-
learning algorithms have been developed for automatic retinal fundus image analysis …

Many machine learning problems can be formulated as non-convex multi-player games.
Due to non-convexity, it is challenging to obtain the existence condition of the global Nash …

This article delves into the intersection of generative AI and digital twins within drug
discovery, exploring their synergistic potential to revolutionize pharmaceutical research and …