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Klarner and Rivest showed that the growth of the number of polyominoes, also known as Klarner's constant, is at most $2+2\sqrt{2}<4.83$ by viewing polyominoes as a sequence of twigs with appropriate weights given to each twig and studying…

Combinatorics · Mathematics 2025-07-15 Vuong Bui

A $d$-dimensional polycube is a facet-connected set of cells (cubes) on the $d$-dimensional cubical lattice $\mathbb{Z}^d$. Let $A_d(n)$ denote the number of $d$-dimensional polycubes (distinct up to translations) with $n$ cubes, and…

Discrete Mathematics · Computer Science 2019-07-02 Gill Barequet , Mira Shalah

Let $P(n)$ be the number of polyominoes of $n$ cells and $\lambda$ be Klarner's constant, that is, $\lambda=\lim_{n\to\infty} \sqrt[n]{P(n)}$. We show that there exist some positive numbers $A,T$, so that for every $n$ \[ P(n) \ge…

Combinatorics · Mathematics 2025-07-15 Vuong Bui

We provide a short and elementary proof that the growth constant of polyiamonds is at most $1+2z+3z^2$ for the unique real root $z$ of the equation $2z^3+z^2-1=0$. This coincidentally suffices to recover the best known upper bound $3.6108$.…

Combinatorics · Mathematics 2026-01-19 Vuong Bui

We give a sharp lower bound on the capacity of a real stable polynomial, depending only on the value of its gradient at $x = 1$. This result implies a sharp improvement to a similar inequality proved by Linial-Samorodnitsky-Wigderson in…

Combinatorics · Mathematics 2022-09-23 Leonid Gurvits , Jonathan Leake

Since the control of the Lipschitz constant has a great impact on the training stability, generalization, and robustness of neural networks, the estimation of this value is nowadays a real scientific challenge. In this paper we introduce a…

Machine Learning · Computer Science 2023-06-21 Blaise Delattre , Quentin Barthélemy , Alexandre Araujo , Alexandre Allauzen

We infer upper and lower bounds on the exponential growth constants $\alpha(\Lambda)$, $\alpha_0(\Lambda)$, and $\beta(\Lambda)$ describing the large-$n$ behavior of, respectively, the number of acyclic orientations, acyclic orientations…

Statistical Mechanics · Physics 2019-10-09 Shu-Chiuan Chang , Robert Shrock

Reconstruction of population histories is a central problem in population genetics. Existing coalescent-based methods, like the seminal work of Li and Durbin (Nature, 2011), attempt to solve this problem using sequence data but have no…

Populations and Evolution · Quantitative Biology 2020-05-11 Younhun Kim , Frederic Koehler , Ankur Moitra , Elchanan Mossel , Govind Ramnarayan

We prove lower bounds of order $n\log n$ for both the problem to multiply polynomials of degree $n$, and to divide polynomials with remainder, in the model of bounded coefficient arithmetic circuits over the complex numbers. These lower…

Computational Complexity · Computer Science 2007-05-23 Peter Buergisser , Martin Lotz

We introduce a new technique proving formula size lower bounds based on the linear programming bound originally introduced by Karchmer, Kushilevitz and Nisan [11] and the theory of stable set polytope. We apply it to majority functions and…

Computational Complexity · Computer Science 2009-02-13 Kenya Ueno

In many high-dimensional problems,polynomial-time algorithms fall short of achieving the statistical limits attainable without computational constraints. A powerful approach to probe the limits of polynomial-time algorithms is to study the…

Statistics Theory · Mathematics 2025-07-11 Bertrand Even , Christophe Giraud , Nicolas Verzelen

The following notion of growth rate can be seen as a generalization of joint spectral radius: Given a bilinear map $*:\mathbb R^d\times\mathbb R^d\to\mathbb R^d$ with nonnegative coefficients and a nonnegative vector $s\in\mathbb R^d$,…

Combinatorics · Mathematics 2025-08-07 Vuong Bui

We establish an improved lower bound of 10.271 for the exponential growth rate of the class of permutations avoiding the pattern 1324, and an improved upper bound of 13.5. These results depend on a new exact structural characterisation of…

Combinatorics · Mathematics 2019-05-13 David Bevan , Robert Brignall , Andrew Elvey Price , Jay Pantone

The Durand-Kerner algorithm is a widely used iterative technique for simultaneously finding all the roots of a polynomial. However, its convergence heavily depends on the choice of initial approximations. This paper introduces two novel…

Numerical Analysis · Mathematics 2025-11-12 B. A. Sanjoyo , M. Yunus , N. Hidayat

We analyze a simple randomized subgradient method for approximating solutions to stochastic systems of convex functional constraints, the only input to the algorithm being the size of minibatches. By introducing a new notion of what is…

Optimization and Control · Mathematics 2021-08-30 James Renegar , Song Zhou

The Recoil Growth algorithm, proposed in 1999 by Consta et al., is one of the most efficient algorithm available in the literature to sample from a multi-polymer system. Such problems are closely related to the generation of self-avoiding…

Computational Engineering, Finance, and Science · Computer Science 2009-07-02 Florian Simatos

This paper examines a novel gradient boosting framework for regression. We regularize gradient boosted trees by introducing subsampling and employ a modified shrinkage algorithm so that at every boosting stage the estimate is given by an…

Methodology · Statistics 2019-09-16 Yichen Zhou , Giles Hooker

The Lipschitz constant is an important quantity that arises in analysing the convergence of gradient-based optimization methods. It is generally unclear how to estimate the Lipschitz constant of a complex model. Thus, this paper studies an…

Machine Learning · Statistics 2023-02-10 Calypso Herrera , Florian Krach , Josef Teichmann

The exponential growth rate of non polynomially growing subgroups of $GL_d$ is conjectured to admit a uniform lower bound. This is known for non-amenable subgroups, while for amenable subgroups it is known to imply the Lehmer conjecture…

Classical Analysis and ODEs · Mathematics 2022-08-25 Emmanuel Breuillard , Péter P. Varjú

Often in the analysis of first-order methods, assuming the existence of a quadratic growth bound (a generalization of strong convexity) facilitates much stronger convergence analysis. Hence the analysis is done twice, once for the general…

Optimization and Control · Mathematics 2019-05-16 Benjamin Grimmer
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