Continuous dequantization embeds discrete data into a continuous space, but relaxation can alter the statistical information carried by the original categories. We study a complementary regime in which a specified weighted discrete law is the target and the dequantizer is required to be lossless under a prescribed quan...
Maha Moussa, Khater A. E. Gad, H. Hamouda et al.· Stats· 0 citations
The condensation method for recovering the circle of camera angles from the COIL image dataset is demonstrated, where a standard PCA pipeline produces spurious homology, and the quotient of views of a tetrahedron in the SYMSOL pose-estimation benchmark is demonstrated.
We consider the probability that the convex hull of the first $n$ partial sums of a $d$-dimensional random walk contains the origin. Under symmetric exchangeability of the increments and a general-position assumption, this absorption probability is distribution-free and admits an explicit formula, previously obtained b...
We study the problem of approximating the John ellipsoid (JE) of a given (centrally symmetric) polytope of $n$ constraints in a Euclidean space under differential privacy (DP). We give the first differentially private algorithm for this problem under the standard model, where neighboring datasets may differ arbitrarily...
It is proved that the induced squared-norm estimator is unbiased up to a term decaying geometrically with a sampling gap, and that its variance is a constant $V_0/m$ that is dimension-free in experiment and, under one stated concentration hypothesis, in theory.
Suppose we are given an ordered sequence of independent data whose distribution changes $K$ times at unknown locations, for some unknown $K \geq 0$. In this paper, we study the problem of performing distribution-free inference on $K$. First, we show an impossibility result: any distribution-free upper confidence bound...
Rohan Hore, Aaditya Ramdas· 0 citations
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