Research in computer analysis of medical images bears many promises to improve patients'
health. However, a number of systematic challenges are slowing down the progress of the …

The comprehensive evaluation of the performance of a recommender system is a complex
endeavor: many facets need to be considered in configuring an adequate and effective …

For a long time, different recommendation tasks require designing task-specific architectures
and training objectives. As a result, it is hard to transfer the knowledge and representations …

Gait recognition is one of the most critical long-distance identification technologies and
increasingly gains popularity in both research and industry communities. Despite the …

Deep learning's recent history has been one of achievement: from triumphing over humans
in the game of Go to world-leading performance in image classification, voice recognition …

Learning effective feature crosses is the key behind building recommender systems.
However, the sparse and large feature space requires exhaustive search to identify effective …

Deep neural networks have been well-known for their superb handling of various machine
learning and artificial intelligence tasks. However, due to their over-parameterized black-box …

Influenced by the great success of deep learning in computer vision and language
understanding, research in recommendation has shifted to inventing new recommender …

This viewpoint article argues that the impacts of the novel coronavirus COVID-19 call for
transformative e-Tourism research. We are at a crossroads where one road takes us to e …

Deep metric learning papers from the past four years have consistently claimed great
advances in accuracy, often more than doubling the performance of decade-old methods. In …