Soni, Akshay; Haupt, Jarvis; Porikli, Fatih
Many machine learning applications employ a multiclass classification stage that uses multiple binary linear classifiers as building blocks. Among these, commonly used strategies such as one-vs-one classification can require learning a large number of hyperplanes, even when the number of classes to be discriminated among is modest. Further, when the data being classified is inherently high-dimensional, the storage and computational complexity associated with the application of multiple linear...[Show more]
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