AI in finance refers to the applications of AI techniques in financial businesses. This area has
attracted attention for decades, with both classic and modern AI techniques applied to …

Recommender systems (RSs) have been playing an increasingly important role for informed
consumption, services, and decision-making in the overloaded information era and digitized …

The 21st century has ushered in the age of big data and data economy, in which data DNA,
which carries important knowledge, insights, and potential, has become an intrinsic …

To recommend the next item to a user in a transactional context is practical yet challenging
in applications such as marketing campaigns. Transactional context refers to the items that …

Learning expressive low-dimensional representations of ultrahigh-dimensional data, eg,
data with thousands/millions of features, has been a major way to enable learning methods …

Privacy preserving on data mining and data release has attracted an increasing research
interest over a number of decades. Differential privacy is one influential privacy notion that …

The recent booming of AI in FinTech evidences the significant developments and potential of
AI for making smart FinTech, economy, finance and society. AI-empowered smart FinTech …

Complex applications such as big data analytics involve different forms of coupling
relationships that reflect interactions between factors related to technical, business (domain …

Background and objective Critical care patient events like sepsis or septic shock in intensive
care units (ICUs) are dangerous complications which can cause multiple organ failures and …

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