sub-Gaussian inequalitiesWe study the problem of estimating the mean of a random vector X given a sample of N independent, identically distributed points. We introduce a new estimator that achieves a purely sub-Gaussian performance under the only condition that the second moment of X exists. The...
We study the problem of estimating the mean of a random vector $X$ given a sample of $N$ independent, identically distributed points. We introduce a new estimator that achieves a purely sub-Gaussian performance under the only condition that the second moment of $X$ exists. The estimator is...
{m imes m} is an m imes m m imes m matrix, and random vector X \\circ \\xi X \\circ \\xi denotes the Hadamard product of an isotropic subgaussian random vector X \\in \\mathbb{R}^m X \\in \\mathbb{R}^m and a random vector \\xi \\in \\{0, 1\\}^m \\xi \\in...
We also investigate a random method to identify exactly any vector which has a relatively short support using linear subgaussian measurements as above. It turns out that our analysis, when applied to $\\{-1,1\\}$-valued vectors with i.i.d, symmetric entries, yields new information on the...
59 Cutoff for Random Walks on Random Graphs at the Entropic Time 24:37 Cutoff for random walks on random graphs at the entropic time 51:32 GMConformal welding in Liouville quantum gravity_ recent results and application 45:28 Grothendeick Lp Problem for Gaussian Matrices 27:01 https___math...
in sub-gaussian random variables.We deduce a useful concentration inequality for sub-gaussian random vectors.Two examples are given to illustrate these results: a concentration of distances between random vectors and subspaces, and a bound on the norms of products of random and deterministic matrices...
This paper considers two sub-optimal transmission schemes for a family of parallel Gaussian vector broadcast channels. One of the schemes is based on the QR precoding of Ginis et al. (2000). In QR precoding, the maximum achievable throughput depends on the order in which users are encoded. ...
MPSVector MPSVectorDescriptor MobileCoreServices ModelIO MonoTouch.Dialog MonoTouch.Dialog.Utilities MonoTouch.NUnit MonoTouch.NUnit.UI MultipeerConnectivity NaturalLanguage Rete NetworkExtension Kit di stampa NotificationCenter NUnit NUnit.Framework NUnit.Framework.Api NUnit.Framework.Builders NUnit.Framework.Co...
In addition to LASSO-COX, four machine learning algorithms commonly used to process survival data, including random survival forests (RSF), survival support vector machine (SVM), gradient boosting survival model (GBS) and extreme gradient boosting survival model (XGB), were also constructed to evalu...
We use in this experiment a Gaussian filter that can be defined in spectral space as: $${G}_{\nu }=\exp \left(-\frac{{\nu }^{2}{\Delta }_{{{\rm{f}}}^{2}}{24}\right),$$ where Δf is the filter size, which is taken to be Δf = 2ΔLES to yield sufficient resolutio...