DSSVD

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8. def dssvd[K](drmA: DrmLike[K], k: Int, p: Int = 15, q: Int = 0, cacheHint: CacheHint = CacheHint.MEMORY_ONLY): (DrmLike[K], DrmLike[Int], Vector)

   Distributed Stochastic Singular Value decomposition algorithm.

   Distributed Stochastic Singular Value decomposition algorithm.

   drmA

   input matrix A

   k

   request SSVD rank

   p

   oversampling parameter

   q

   number of power iterations

   returns

   (U,V,s). Note that U, V are non-checkpointed matrices (i.e. one needs to actually use them e.g. save them to hdfs in order to trigger their computation.

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