This paper presents a language-powered paradigm for ordinal regression. Existing methods
usually treat each rank as a category and employ a set of weights to learn these concepts …

Learning from a label distribution has achieved promising results on ordinal regression
tasks such as facial age and head pose estimation wherein, the concept of adaptive label …

Consensus clustering provides an elegant framework to aggregate multiple weak clustering
results to learn a consensus one that is more robust and stable than a single result …

By utilizing the complementary information from multiple views, multi-view clustering (MVC)
algorithms typically achieve much better clustering performance than conventional single …

Adversarial training is considered one of the most effective methods to improve the
adversarial robustness of deep neural networks. Despite the success, it still suffers from …

Label distribution learning (LDL) has achieved great progress in facial expression
recognition (FER), where the generating label distribution is a key procedure for LDL-based …

A shared goal of several machine learning communities like continual learning, meta-
learning and transfer learning, is to design algorithms and models that efficiently and …

Clustering is a crucial but challenging task in data mining and machine learning. Recently,
deep clustering, which derives inspiration primarily from deep learning approaches, has …

We present a multitask network that supports various deep neural network based pedestrian
detection functions. Besides 2D and 3D human pose, it also supports body and head …

Facial age estimation has attracted considerable attention owing to its great potential in
applications. However, it still falls short of reliable age estimation due to the lack of sufficient …