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Testing mutual independence among several random vectors of arbitrary dimensions is a challenging problem in Statistics, and it has gained considerable interest in recent years. In this article, we propose some nonparametric tests based on different notion ...
Suppose we are given two independent strings of data from a known finite alphabet. We are interested in testing the null hypothesis that both the strings were drawn from the same distribution, assuming that the samples within each string are mutually indep ...
In this paper, we study the redundancy of Huffman codes. In particular, we consider sources for which the probability of one of the source symbols is known. We prove a conjecture of Ye and Yeung regarding the upper bound on the redundancy of such Huffman c ...
Kinetic models are essential for studying complex behavior and properties of metabolism. However, a persistent hurdle for constructing these models is uncertainty in the kinetic properties of enzymes. Currently available methods for building kinetic models ...
We address the maximization of a project’s expected net present value when the activity durations and cash flows are described by a discrete set of alternative scenarios with associated occurrence probabilities. In this setting, the choice of scenario-inde ...
We present an experimental study of the complete in-plane dynamics of capillary self-alignment. The two translational (shift) and single rotational (twist) in-plane modes of square millimetric transparent dies bridged to shape-matching receptor sites throu ...
We consider multiple access communication on a binary input additive white Gaussian noise channel using randomly spread code division. For a general class of symmetric distributions for spreading coefficients, in the limit of a large number of users, we pr ...
Objectives To determine and compare the qualitative and quantitative diagnostic performance of a single sagittal fast spin echo (FSE) T2-weighted Dixon sequence in differentiating benign and malignant vertebral compression fractures (VCF), using multiple r ...
Testing for mutual independence among several random vectors is a challenging problem, and in recent years, it has gained significant attention in statistics and machine learning literature. Most of the existing tests of independence deal with only two ran ...
Bounding the generalization error of learning algorithms has a long history, which yet falls short in explaining various generalization successes including those of deep learning. Two important difficulties are (i) exploiting the dependencies between the h ...
