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.
KeywordsRandom Matrix Rejection Rate Conditional Density Uniform Sample Spectral Norm
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