From Caesar Cipher to Unsupervised Learning: A New Method for Classifier Parameter Estimation

6 Jun 2019Yu LiuLi DengJianshu ChenChang Wen Chen

Many important classification problems, such as object classification, speech recognition, and machine translation, have been tackled by the supervised learning paradigm in the past, where training corpora of parallel input-output pairs are required with high cost. To remove the need for the parallel training corpora has practical significance for real-world applications, and it is one of the main goals of unsupervised learning... (read more)

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