Feature models are the de facto standard for modelling variabilities and commonalities in
features and relationships in software product lines. They are the base artefacts in many …

Feature models are the" de facto" standard for variability modelling and are used in both
academia and industry. The MODEVAR initiative tries to establish a common textual feature …

In meta-learning, the knowledge learned from previous tasks is transferred to new ones, but
this transfer only works if tasks are related. Sharing information between unrelated tasks …

To enable effective learning of new tasks with only a few examples, meta-learning acquires
common knowledge from the existing tasks with a globally shared meta-learner. To further …

In many real-world tasks, a canonical" big data" problem is created by combining data from
several individual groups or domains. Because test data will likely come from a new group of …

The goal of Artificial Intelligence (AI) research is to develop a system that not only performs
tasks comparably to humans (eg, understanding language and vision) but also learns new …

Artificial intelligence (AI) promises powerful new capabilities in an expansive array of
applications. One area is proliferation detection, where AI can provide transformative tools to …

In meta-learning, the knowledge learned from previous tasks is transferred to new ones, but
this transfer only works if tasks are related. Sharing information between unrelated tasks …

Deep learning methods have achieved significant success when trained on large amounts
of data. However, in many real-world applications, data are either too expensive or …

Deep learning methods have shown unparalleled performance when trained on vast
amounts of diverse labeled training data, often collected at great cost. In many contexts, we …