
Continuous Terrain Guarding with TwoSided Guards
Herein, we consider the continuous 1.5dimensional(1.5D) terrain guardin...
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Stationarity in the Realizations of the Causal RateDistortion Function for OneSided Stationary Sources
This paper derives novel results on the characterization of the the caus...
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From the Bernoulli Factory to a Dice Enterprise via Perfect Sampling of Markov Chains
Given a pcoin that lands heads with unknown probability p, we wish to p...
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Reply to Chen et al.: Parametric methods for cluster inference perform worse for twosided ttests
Onesided ttests are commonly used in the neuroimaging field, but twos...
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Adaptive Combinatorial Allocation
We consider settings where an allocation has to be chosen repeatedly, re...
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Analysis of the Effect of Unexpected Outliers in the Classification of Spectroscopy Data
Multiclass classification algorithms are very widely used, but we argue...
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Monotonicity of the TraceInverse of Covariance Submatrices and TwoSided Prediction
It is common to assess the "memory strength" of a stationary process loo...
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An Orthogonality Principle for SelectMaximum Estimation of Exponential Variables
It was recently proposed to encode the onesided exponential source X into K parallel channels, Y1, ..., YK , such that the error signals X  Yi, i = 1,...,K, are onesided exponential and mutually independent given X [1], [2]. Moreover, it was shown that the optimal estimator Ŷ of the source X with respect to the onesided error criterion, is simply given by the maximum of the outputs, i.e., Ŷ = maxY1,..., YK. In this paper, we show that the distribution of the resulting estimation error X  Ŷ , is equivalent to that of the optimum noise in the backward testchannel of the onesided exponential source, i.e., it is onesided exponentially distributed and statistically independent of the joint output Y1,...,YK.
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