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We give general lower bounds on the maximal determinant ofn×n{+1,−1}matrices, both with and without the assumption of the Hadamard conjecture. Our bounds improve on earlier resultsof de Launey a...
For estimating a lower bounded parametric function in the framework of Marchand and Strawderman(2006), we provide “through” a unified approach a class of Bayesian confidence intervals with credibility...
We present an argument based on the multidimensional and the uniform central limit theorems, proving that, under some geometrical assumptions between the target function $T$ and the learning class $F$...
In this paper we derive lower bounds in minimax sense for estimation of the instantaneous volatility if the diffusion type part cannot be observed directly but under some additional Gaussian noise. ...
A new lower bound involving f-divergences between the underlying probability measures is proved for the minimax risk in estimation problems. The proof just uses the convexity of the function f and ...
Exact lower bounds on the exponential moments of min(y,X) and X I {X < y} are provided given the first two moments of a random variable X. These bounds are useful in work on large deviations probabi...
Upper bounds for rates of convergence of posterior distributions associated to Gaussian process priors are obtained by van der Vaart and van Zanten in [van der Vaart and van Zanten, Rates of contracti...

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