Matrix Randomization Methods
This chapter presents algorithms for uniform matrix sample generation in norm-bounded sets. First, we discuss the simple case of matrix sampling in sets defined by ℓ p Hilbert–Schmidt norm, which reduces to the vector ℓ p norm randomization problem. Subsequently, we present an efficient solution to the problem of uniform generation in sets defined by the spectral norm.
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