Cited by 40.3kOpen Access
Google (United States)
Publishes on Machine Learning and Algorithms, Domain Adaptation and Few-Shot Learning, Machine Learning and Data Classification. 141 papers and 83.3k citations.
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This paper compares the performance of several classifier algorithms on a standard database of handwritten digits. We consider not only raw accuracy, but also training time, recognition time, and memory requirements. When available, we report measurements of the fraction of patterns that must be rejected so that the remaining patterns have misclassification rates less than a given threshold.