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Adapting machine Learning to non-stationary environments

Donnie, Wintheiser
Adapting machine Learning to non-stationary environments
Machine learning stimulates a broad range of computational methods that exploit experience, which typically takes the form of electronic data, to make profitable decisions or accurate predictions. To date, the machine learning models have been applied to extensive application domains across diverse fields, including but not limited to computer vision [1, 2, 3], natural language processing [4, 5, 6], robotic control [7, 8], and cyber security [...

CHF 38.50