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A unified framework for high-dimensional analysis of $M$-estimators with decomposable regularizers
unified framework high-dimensional analysis $M$-estimators decomposable regularizers
2010/10/19
High-dimensional statistical inference deals with models in which the the number of parameters $p$ is comparable to or larger than the sample size $n$. Since it is usually impossible to obtain consist...
We study the problem of learning a sparse linear regression vector under additional conditions on the structure of its sparsity pattern. This problem is relevant in machine learning, statistics and s...