Concepts have been adopted in concept-cognitive learning (CCL) and conceptual clustering
for concept classification and concept discovery. However, the standard CCL algorithms are …

Abstract Electronic Health Records (EHRs) contain rich information of patient health status,
which usually include both structured and unstructured data. There have been many studies …

In this work we propose a multi-task spatio-temporal network, called SUSiNet, that can jointly
tackle the spatio-temporal problems of saliency estimation, action recognition and video …

Conversations on social media tend to go off-topic and turn into different and sometimes
toxic exchanges. Previous work focuses on analysing textual dialogues that have derailed …

People can often acquire knowledge dynamically and rapidly from different types of data, yet
existing incremental learning algorithms are still computationally time consuming and most …

Since acquiring pixel-wise annotations for training convolutional neural networks for
semantic image segmentation is time-consuming, weakly supervised approaches that only …

In general, visual media comprises a set of elements of basic semantics, named
fundamental visual concepts, that may not be semantically decomposed, such as objects …

With the rapid development of machine learning models along with increasingly complex
data structures, it becomes difficult to ground the reliability of models' predictions despite the …

We propose a task called Visual Concept Naming to associate visual concepts with the
corresponding textual expressions, ie, names of visual concepts found in real-world …

An extensive investigation into the usefulness of probabilistic and fuzzy logic approaches to
natural language semantics is presented here. Natural Language Processing (NLP) has …