The rising popularity of explainable artificial intelligence (XAI) to understand high-performing
black boxes raised the question of how to evaluate explanations of machine learning (ML) …

Recommender systems have become crucial in information filtering nowadays. Existing
recommender systems extract user preferences based on the correlation in data, such as …

Multi-task learning (MTL) has been successfully applied to many recommendation
applications. However, MTL models often suffer from performance degeneration with …

Purpose The transition to omnichannel retail is the recognized future of retail, which uses
digital technologies (eg augmented reality shop** assistants) to enhance the customer …

Explainable recommendation attempts to develop models that generate not only high-quality
recommendations but also intuitive explanations. The explanations may either be post-hoc …

By providing explanations for users and system designers to facilitate better understanding
and decision making, explainable recommendation has been an important research …

In this paper, we introduce a large scale multi-objective ranking system for recommending
what video to watch next on an industrial video sharing platform. The system faces many …