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作者：Tang, Yu; Xu, Hongquan
作者单位：Soochow University - China; University of California System; University of California Los Angeles
摘要：While the minimum aberration criterion is popular for selecting good designs with qualitative factors under an ANOVA model, the minimum beta-aberration criterion is more suitable for selecting designs with quantitative factors under a polynomial model. In this paper, we propose the concept of wordlength enumerator to unify these two criteria. The wordlength enumerator is defined as an average similarity of contrasts among all possible pairs of runs. The wordlength enumerator is easy and fast t...
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作者：Kim, Ilmun; Ramdas, Aaditya; Singh, Aarti; Wasserman, Larry
作者单位：Carnegie Mellon University
摘要：When data analysts train a classifier and check if its accuracy is significantly different from chance, they are implicitly performing a two-sample test. We investigate the statistical properties of this flexible approach in the high-dimensional setting. We prove two results that hold for all classifiers in any dimensions: if its true error remains epsilon-better than chance for some epsilon > 0 as d, n -> infinity, then (a) the permutation-based test is consistent (has power approaching to on...
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作者：Kleijn, B. J. K.
作者单位：University of Amsterdam
摘要：To the frequentist who computes posteriors, not all priors are useful asymptotically: in this paper, a Bayesian perspective on test sequences is proposed and Schwartz's Kullback-Leibler condition is generalised to widen the range of frequentist applications of posterior convergence. With Bayesian tests and a weakened form of contiguity termed remote contiguity, we prove simple and fully general frequentist theorems, for posterior consistency and rates of convergence, for consistency of posteri...
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作者：Lugosi, Gabor; Mendelson, Shahar
作者单位：ICREA; Pompeu Fabra University; Australian National University
摘要：We consider the problem of estimating the mean of a random vector based on i.i.d. observations and adversarial contamination. We introduce a multivariate extension of the trimmed-mean estimator and show its optimal performance under minimal conditions.
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作者：Cai, T. Tony; Wei, Hongji
作者单位：University of Pennsylvania
摘要：Human learners have the natural ability to use knowledge gained in one setting for learning in a different but related setting. This ability to transfer knowledge from one task to another is essential for effective learning. In this paper, we study transfer learning in the context of nonparametric classification based on observations from different distributions under the posterior drift model, which is a general framework and arises in many practical problems. We first establish the minimax r...
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作者：Efromovich, Sam
作者单位：University of Texas System; University of Texas Dallas
摘要：Nonparametric estimation of the cumulative distribution function and the probability density of a lifetime X modified by a current status censoring (CSC), including cases of right and left missing data, is a classical ill-posed problem with biased data. The biased nature of CSC data may preclude us from consistent estimation unless the biasing function is known or may be estimated, and its ill-posed nature slows down rates of convergence. Under a traditionally studied CSC, we observe a sample ...
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作者：Bao, Zhigang; Ding, Xiucai; Wang, Ke
作者单位：Hong Kong University of Science & Technology; University of California System; University of California Davis
摘要：In this paper, we study the matrix denoising model Y = S + X, where S is a low rank deterministic signal matrix and X is a random noise matrix, and both are M x n. In the scenario that M and n are comparably large and the signals are supercritical, we study the fluctuation of the outlier singular vectors of Y, under fully general assumptions on the structure of S and the distribution of X. More specifically, we derive the limiting distribution of angles between the principal singular vectors o...
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作者：Wang, Daren; Yu, Yi; Rinaldo, Alessandro
作者单位：University of Chicago; University of Warwick; Carnegie Mellon University
摘要：We study the problem of change point localization in dynamic networks models. We assume that we observe a sequence of independent adjacency matrices of the same size, each corresponding to a realization of an unknown inhomogeneous Bernoulli model. The underlying distribution of the adjacency matrices are piecewise constant, and may change over a subset of the time points, called change points. We are concerned with recovering the unknown number and positions of the change points. In our model ...
