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A Unified Near-Optimal Estimator For Dimension Reduction in lα (0 < α ≤ 2) Using Stable Random Projections
Near-Optimal Estimator Dimension Reduction Stable Random Projections
2015/8/21
Many tasks (e.g., clustering) in machine learning only require the lα distances instead of the original data. For dimension reductions in the lα norm (0 < α ≤ 2), the method of stable random projectio...
Nonlinear Estimators and Tail Bounds for Dimension Reduction in l1 Using Cauchy Random Projections
dimension reduction l1 norm Johnson-Lindenstrauss (JL) lemma Cauchy random projections
2015/8/21
For1 dimension reduction in the l1 norm, the method of Cauchy random projections multiplies the original data matrix A ∈ Rn×D with a random matrix R ∈ RD×k (k D) whose entries are i.i.d. samples of ...
Lossless Linear Compression of Data with Minimal Dimension in Linear Minimum Variance Estimation
LMV estimation lossless compression linear transformation singular value
2011/11/11
Consider a Linear Minimum Variance (LMV) estimation problem where the linear transformation of data is needed to compress dimension of observation data without loss of performance. A necessary and su±...
On blocks stably equivalent to a quantum complete intersection of dimension 9 in characteristic 3 and a case of the abelian defect group conjecture
On blocks stably equivalent to a quantum complete intersection of dimension 9 characteristic abelian defect group conjecture
2011/1/17
Using a stable equivalence due to Rouquier, we prove that Brou´e’s abelian defect group conjecture holds for 3-blocks of defect 2 whose Brauer correspondent has a unique isomorphism class of sim...