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We introduce online learning algorithms which are independent of feature scales, proving regret bounds dependent on the ratio of scales existent in the data rather than the absolute scale. This has se...
Limiting distributions and almost sure limit theorems for the normalized maxima of complete and incomplete samples from Gaussian sequence
complete and incomplete samples limiting distribution maximum stationary Gaussian sequence
2009/9/16
Let ${X_k, kgeqslant 1}$ be a stationary Gaussian sequence with partial maximum $M_n=max{X_{k},1leqslant kleqslant n}$ and sample mean $overline{X}_n=sum_{k=1}^{n}X_{k}/n$. Suppose that some of the ra...