On kissing numbers and spherical codes in high dimensions
Sign Up to like & getrecommendations! Published in 2018 at "Advances in Mathematics"
DOI: 10.1016/j.aim.2018.07.001
Abstract: We prove a lower bound of $\Omega (d^{3/2} \cdot (2/\sqrt{3})^d)$ on the kissing number in dimension $d$. This improves the classical lower bound of Chabauty, Shannon, and Wyner by a linear factor in the dimension.… read more here.
Keywords: codes high; spherical codes; high dimensions; numbers spherical ... See more keywords
An ADMM with continuation algorithm for non-convex SICA-penalized regression in high dimensions
Sign Up to like & getrecommendations! Published in 2018 at "Journal of Statistical Computation and Simulation"
DOI: 10.1080/00949655.2018.1448397
Abstract: Abstract The smooth integration of counting and absolute deviation (SICA) penalty has been demonstrated theoretically and practically to be effective in non-convex penalization for variable selection. However, solving the non-convex optimization problem associated with the… read more here.
Keywords: sica penalized; convex; high dimensions; continuation algorithm ... See more keywords
Bypassing sluggishness: SWAP algorithm and glassiness in high dimensions.
Sign Up to like & getrecommendations! Published in 2019 at "Physical review. E"
DOI: 10.1103/physreve.99.031301
Abstract: The recent implementation of a swap Monte Carlo algorithm (SWAP) for polydisperse glass forming mixtures bypasses computational sluggishness and closes the gap between experimental and simulation timescales in physical dimensions d=2 and 3. Here, we… read more here.
Keywords: bypassing sluggishness; swap; swap algorithm; high dimensions ... See more keywords
Canonical correlation analysis in high dimensions with structured regularization
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DOI: 10.1177/1471082x211041033
Abstract: Canonical correlation analysis (CCA) is a technique for measuring the association between two multivariate data matrices. A regularized modification of canonical correlation analysis (RCCA) which imposes an [Formula: see text] penalty on the CCA coefficients… read more here.
Keywords: high dimensions; correlation analysis; canonical correlation; regularization ... See more keywords
Group inference in high dimensions with applications to hierarchical testing
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DOI: 10.1214/21-ejs1955
Abstract: Group inference has been a long-standing question in statistics and the development of high-dimensional group inference is an essential part of statistical methods for analyzing complex data sets, including hierarchical testing, tests of interaction, detection… read more here.
Keywords: group; inference high; group inference; high dimensions ... See more keywords
The Gaussian core model in high dimensions
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DOI: 10.1215/00127094-2018-0018
Abstract: We prove lower bounds for energy in the Gaussian core model, in which point particles interact via a Gaussian potential. Under the potential function $t \mapsto e^{-\alpha t^2}$ with $0 \pi e$. As a consequence… read more here.
Keywords: high dimensions; core model; gaussian core; model high ... See more keywords
A robust and nonparametric two-sample test in high dimensions
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DOI: 10.5705/ss.202019.0170
Abstract: Many tests are proposed in the literature to test homogeneity of two random samples, that is, the exact equivalence of their statistical distributions. When the two random samples are high-dimensional or not normally distributed, the… read more here.
Keywords: nonparametric two; high dimensions; two sample; test ... See more keywords