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A numerical semigroup is an additive subsemigroup of the non-negative integers. In this paper, we consider parametrized families of numerical semigroups of the form $P_n = \langle f_1(n), \ldots, f_k(n) \rangle$ for polynomial functions…

Commutative Algebra · Mathematics 2020-05-20 Franklin Kerstetter , Christopher O'Neill

Let $\{f_j\}_{j=0}^n$ be a sequence of orthonormal polynomials where the orthogonality relation is satisfied on either the real line or on the unit circle. We study zero distribution of random linear combinations of the form…

Classical Analysis and ODEs · Mathematics 2018-02-12 Aaron Yeager

We consider mixtures of $k\geq 2$ Gaussian components with unknown means and unknown covariance (identical for all components) that are well-separated, i.e., distinct components have statistical overlap at most $k^{-C}$ for a large enough…

Machine Learning · Computer Science 2023-06-09 Rares-Darius Buhai , David Steurer

A result of Simonovits and S\'os states that for any fixed graph $H$ and any $\epsilon > 0$ there exists $\delta > 0$ such that if $G$ is an $n$-vertex graph with the property that every $S \subseteq V(G)$ contains $p^{e(H)} |S|^{v(H)} \pm…

Combinatorics · Mathematics 2016-12-23 David Conlon , Jacob Fox , Benny Sudakov

Efficient simulation of stochastic partial differential equations (SPDE) on general domains requires noise discretization. This paper employs piecewise linear interpolation of noise in a fully discrete finite element approximation of a…

Numerical Analysis · Mathematics 2024-10-22 Gabriel Lord , Andreas Petersson

The accuracy of applying density functional theory to noncovalent interactions is hindered by errors arising from low-density regions of interaction-induced change in the density gradient, error compensation between correlation and exchange…

Chemical Physics · Physics 2014-10-22 Marcin Modrzejewski , Grzegorz Chałasiński , Małgorzata M. Szczęśniak

We present an algorithm for testing halfspaces over arbitrary, unknown rotation-invariant distributions. Using $\tilde O(\sqrt{n}\epsilon^{-7})$ random examples of an unknown function $f$, the algorithm determines with high probability…

Data Structures and Algorithms · Computer Science 2018-11-02 Nathaniel Harms

For $X(n)$ a Rademacher or Steinhaus random multiplicative function, we consider the random polynomials $$ P_N(\theta) = \frac1{\sqrt{N}} \sum_{n\leq N} X(n) e(n\theta), $$ and show that the $2k$-th moments on the unit circle $$ \int_0^1…

Number Theory · Mathematics 2023-11-23 Jacques Benatar , Alon Nishry , Brad Rodgers

We study almost sure separating and interpolating properties of random sequences in the polydisc and the unit ball. In the unit ball, we obtain the 0-1 Komolgorov law for a sequence to be interpolating almost surely for all the…

Complex Variables · Mathematics 2021-07-13 Alberto Dayan , Brett D. Wick , Shengkun Wu

Let $f$ be a semi-weighted-homogeneous polynomial having an isolated singularity at 0. Let $\alpha_{f,k}$ be the spectral numbers of $f$ at 0. By Malgrange and Varchenko there are non-negative integers $r_k$ such that the $\alpha_{f,k}-r_k$…

Algebraic Geometry · Mathematics 2023-02-17 Morihiko Saito

We investigate the combinatorial discrepancy of geometric set systems having bounded shallow cell complexity in the \emph{Beck-Fiala} setting, where each point belongs to at most $t$ ranges. For set systems with shallow cell complexity…

Computational Geometry · Computer Science 2023-01-10 Kunal Dutta , Arijit Ghosh

We study zero distribution of random linear combinations of the form $$P_n(z)=\sum_{j=0}^n\eta_jf_j(z),$$ in any Jordan region $\Omega \subset \mathbb C$. The basis functions $f_j$ are entire functions that are real-valued on the real line,…

Probability · Mathematics 2016-08-08 Aaron Yeager

We provide a new family of $K_k$-free pseudorandom graphs with edge density $\Theta(n^{-1/(k-1)})$, matching a recent construction due to Bishnoi, Ihringer and Pepe. As in the former result, the idea is to use large subgraphs of polarity…

Combinatorics · Mathematics 2021-05-11 Sam Mattheus , Francesco Pavese

We show that on every product probability space, Boolean functions with small total influences are essentially the ones that are almost measurable with respect to certain natural sub-sigma algebras. This theorem in particular describes the…

Combinatorics · Mathematics 2011-11-15 Hamed Hatami

We show hardness of improperly learning halfspaces in the agnostic model, both in the distribution-independent as well as the distribution-specific setting, based on the assumption that worst-case lattice problems, such as GapSVP or SIVP,…

Machine Learning · Computer Science 2023-02-21 Stefan Tiegel

This paper derives central limit and bootstrap theorems for probabilities that sums of centered high-dimensional random vectors hit hyperrectangles and sparsely convex sets. Specifically, we derive Gaussian and bootstrap approximations for…

Statistics Theory · Mathematics 2016-03-09 Victor Chernozhukov , Denis Chetverikov , Kengo Kato

We study almost symmetric semigroups generated by odd integers. If the embedding dimension is four, we characterize when a symmetric semigroup that is not complete intersection or a pseudo-symmetric semigroup is generated by odd integers.…

Commutative Algebra · Mathematics 2019-01-04 Francesco Strazzanti , Kei-ichi Watanabe

This paper develops a fully discrete soft thresholding polynomial approximation over a general region, named Lasso hyperinterpolation. This approximation is an $\ell_1$-regularized discrete least squares approximation under the same…

Numerical Analysis · Mathematics 2021-08-31 Congpei An , Hao-Ning Wu

For materials which are incorrectly predicted by density functional theory to be metallic, an iterative procedure must be adopted in order to perform GW calculations. In this paper we test two iterative schemes based on the quasi-particle…

Materials Science · Physics 2007-05-23 V. A. Popa , G. Brocks , P. J. Kelly

We study the fine-grained uniform convergence behavior of halfspaces beyond worst-case VC bounds. For inhomogeneous halfspaces in $\mathbb{R}^d$ with $d\ge 2$, we show that standard first-order VC bounds are essentially tight: even…

Machine Learning · Computer Science 2026-05-08 Aryeh Kontorovich , Kasper Green Larsen