Tests which have monetary research let you know expert results of the suggested method regarding newest basic patterns. We consider a class away from embeddings centered on structured haphazard matrices having orthogonal rows that is applied in several host learning software and dimensionality reduction and you can kernel approximation. For the Johnson-Lindenstrauss alter as well as the angular kernel, we show that we can come across matrices producing guaranteed enhanced overall performance within the reliability and/or speed than the before actions. We expose matrices having complex entries which offer extreme next reliability improvement. We offer geometric and Markov chain-based viewpoints to aid see the benefits, and you will empirical results which advise that the fresh means is effective inside the a wider listing of programs.
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