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Tom Michael Mitchell (born August 9, 1951) is an American computer scientist and the Founders University Professor at Carnegie Mellon University (CMU). He is a founder and former chair of the Machine Learning Department at CMU. [4]
Co-training is a machine learning algorithm used when there are only small amounts of labeled data and large amounts of unlabeled data. One of its uses is in text mining for search engines. It was introduced by Avrim Blum and Tom Mitchell in 1998.
CPL is an approach to semi-supervised learning that yields more accurate results by coupling the training of many information extractors. Basic idea behind CPL is that semi-supervised training of a single type of extractor such as ‘coach’ is much more difficult than simultaneously training many extractors that cover a variety of inter-related entity and relation types.
Tom M. Mitchell provided a widely quoted, more formal definition of the algorithms studied in the machine learning field: "A computer program is said to learn from experience E with respect to some class of tasks T and performance measure P if its performance at tasks in T, as measured by P, improves with experience E."
Never-Ending Language Learning system (NELL) is a semantic machine learning system that as of 2010 was being developed by a research team at Carnegie Mellon University, and supported by grants from DARPA, Google, NSF, and CNPq with portions of the system running on a supercomputing cluster provided by Yahoo!.
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Mitchell argues that achieving superintelligence would require that machines acquire commonsense reasoning abilities that are nowhere in sight: "Today's AI is far from general intelligence, and I don’t believe that machine 'superintelligence' is anywhere on the horizon." Mitchell addresses 13 pages to "Trustworthy and Ethical AI".
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