Bayesian Program Learning Framework Advances Machine Learning

Machine learning is all about being able to teach computers how to “grasp” new concepts, but it often requires hundreds of examples during hours of training – all in all, a pretty inefficient process. But that’s up for change thanks to a new piece of research published on Friday. In an attempt of shortening the learning process and transform it in something more alike to human thinking, a team of researchers has developed a Bayesian Program Learning framework. It only needs a few examples in order to apply new concepts and bits of knowledge, and the goal is to then teach computers to detect and replicate handwritten characters based on only one example. There’s a great difference between the standard pattern-recognition algorithms – which present concepts in the form of…


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