The definition and measurement of information is fundamental to methods for information retrieval, text mining, and machine learning.
An empirical study of DLITE loss and the effect of loss-function choice on AI-driven named entity recognition.
New Information Theory (DLITE) exhibiting properties as an information-theoretic measure and as a metric distance function, including triangular inequality.
Machine learning, deep reinforcement learning, training and fine tuning with DLITE loss.