Richard Osei-Adu

Sentiment and emotion in financial journalism: a corpus-based, cross-linguistic analysis of the effects of COVID Humanities and Social Sciences Communications By gradual learning, GML can effectively bridge distribution alignment between labeled training data and unlabeled target data. GML has been successfully applied to the task of Aspect-Level Sentiment Analysis (ALSA)6,7 as well as entity resolution8.

Hong Kong issues generative AI guidelines to banks to avoid bias against consumers South China Morning Post While GenAI has tremendous potential, there are emergent risks, especially in areas such as data confidentiality, GenAI hallucination, bias, toxicity and cyber security. We will continue to enhance our existing AI and machine learning risk framework to cater

What is AI? Everything to know about artificial intelligence (2) IDaRS shares similar assumptions with Vanilla, involving training a model on image patches in a fully supervised manner and assigning the image’s label to its patches52. However, unlike Vanilla, where all extracted patches are used in training, IDaRS employs a selection procedure. Only informative patches