TECHNIQUES FOR SEMI-SUPERVISED TRAINING AND ASSOCIATED APPLICATIONS

摘要

Described herein are semi- supervised machine learning techniques and associated computer- implemented applications. Some aspects provide a system configured to identify associations among data input to the system. In some embodiments, the system may map the input data to one or more vector spaces, such that associated groups of the input data form associated clusters in the vector space(s). For example, the mapping may be performed by one or more trained encoders (e.g., neural network encoders) of the system. Accordingly, a distance separating two data entries in a space may indicate a likelihood of association among the data entries. Various applications of such systems are described herein.