English
Related papers

Related papers: A Note on the Polynomial Ergodicity of the One-Dim…

200 papers

Recently, there has been significant progress in the development of distributed first order methods. (At least) two different types of methods, designed from very different perspectives, have been proposed that achieve both exact and linear…

Information Theory · Computer Science 2017-12-27 Dusan Jakovetic

A fast algorithm to study one-dimensional self-gravitating systems, and, more generally, systems that are Lagrangian integrable between collisions, is presented. The algorithm is event-driven, and uses a heap-ordered set of predicted future…

Disordered Systems and Neural Networks · Physics 2007-05-23 Alain Noullez , Duccio Fanelli , Erik Aurell

Let A be a finite dimensional algebra over a field of characteristic zero graded by a finite abelian group G. Here we study a growth function related to the graded polynomial identities satisfied by A by computing the exponential rate of…

Rings and Algebras · Mathematics 2009-03-12 Eli Aljadeff , Antonio Giambruno , Daniela La Mattina

Following Schweiger's generalization of multidimensional continued fraction algorithms, we consider a very large family of $p$-adic multidimensional continued fraction algorithms, which include Schneider's algorithm, Ruban's algorithms, and…

Dynamical Systems · Mathematics 2021-06-09 Hui Rao , Shin-ichi Yasutomi

We provide a representation in terms of certain canonical functions for a sequence of polynomials orthogonal with respect to a weight that is strictly positive and analytic on the unit circle. These formulas yield a complete asymptotic…

Classical Analysis and ODEs · Mathematics 2007-05-23 A. Martinez-Finkelshtein , K. T. -R. McLaughlin , E. B. Saff

A triangulation is called $z$-knotted if it has a single zigzag (up to reversing). A $z$-orientation on a triangulation is a minimal collection of zigzags which double covers the set of edges. An edge is of type I if zigzags from the…

Combinatorics · Mathematics 2020-08-20 Adam Tyc

Given a projective variety X defined over a finite field, the zeta function of divisors attempts to count all irreducible, codimension one subvarieties of X, each measured by their projective degree. When the dimension of X is greater than…

Number Theory · Mathematics 2008-08-04 C. Douglas Haessig

For general (1+1)-affine Markov processes, we prove the ergodicity and exponential ergodicity in total variation distances. Our methods follow the arguments of ergodic properties for L\'{e}vy-driven OU-processes and a coupling of…

Probability · Mathematics 2021-04-27 Shukai Chen , Zenghu Li

We consider the complexity of equivalence and learning for multiplicity tree automata, i.e., weighted tree automata over a field. We first show that the equivalence problem is logspace equivalent to polynomial identity testing, the…

Machine Learning · Computer Science 2014-12-01 Ines Marusic , James Worrell

In this paper, we derive rates of convergence in the high-dimensional central limit theorem for Polyak-Ruppert averaged iterates generated by the asynchronous Q-learning algorithm with a polynomial stepsize $k^{-\omega},\, \omega \in (1/2,…

Machine Learning · Statistics 2026-04-09 Artemy Rubtsov , Sergey Samsonov , Vladimir Ulyanov , Alexey Naumov

One-dimensional adaptive Fourier decomposition, abbreviated as 1-D AFD, or AFD, is an adaptive representation of a physically realizable signal into a linear combination of parameterized Szeg\"o and higher order Szeg\"o kernels of the…

Complex Variables · Mathematics 2015-03-19 Tao Qian

We revisit the classical problem of optimal experimental design (OED) under a new mathematical model grounded in a geometric motivation. Specifically, we introduce models based on elementary symmetric polynomials; these polynomials capture…

Statistics Theory · Mathematics 2017-05-30 Zelda Mariet , Suvrit Sra

Features in machine learning problems are often time-varying and may be related to outputs in an algebraic or dynamical manner. The dynamic nature of these machine learning problems renders current higher order accelerated gradient descent…

Optimization and Control · Mathematics 2019-05-29 Joseph E. Gaudio , Travis E. Gibson , Anuradha M. Annaswamy , Michael A. Bolender

Consider a class of skew product transformations consisting of an ergodic or a periodic transformation on a probability space (M, B, m) in the base and a semigroup of transformations on another probability space (W,F,P) in the fibre. Under…

Dynamical Systems · Mathematics 2007-10-08 Julia Brettschneider

This paper focuses on the further development of the Lie bracket approximation approach for extremum seeking systems. Classical results in this area provide extremum seeking algorithms with exponential convergence rates for quadratic-like…

Optimization and Control · Mathematics 2025-10-28 Victoria Grushkovskaya , Sameh A. Eisa

Transfer learning has become an essential technique to exploit information from the source domain to boost performance of the target task. Despite the prevalence in high-dimensional data, heterogeneity and heavy tails are insufficiently…

Machine Learning · Statistics 2023-11-07 Jiayu Huang , Mingqiu Wang , Yuanshan Wu

Magnetic moments near zigzag edges in graphene allow complex nanostructures with customised spin properties to be realised. However, computational costs restrict theoretical investigations to small or perfectly periodic structures. Here we…

Mesoscale and Nanoscale Physics · Physics 2022-09-14 Meriç E. Kucukbas , Seán McCann , Stephen R. Power

We consider multiple orthogonal polynomials associated with the exponential cubic weight e^{-x^3} over two contours in the complex plane. We study the basic properties of these polynomials, including the Rodrigues formula and…

Classical Analysis and ODEs · Mathematics 2015-02-05 Walter Van Assche , Galina Filipuk , Lun Zhang

The voltage-conductance kinetic equation for an ensemble of neurons has been studied by many scientists and mathematicians, while its rigorous analysis is still at a premature stage. In this work, we obtain for the first time the…

Probability · Mathematics 2023-05-09 Xu'an Dou , Fanhao Kong , Weijun Xu , Zhennan Zhou

Greedy algorithms have long been a workhorse for learning graphical models, and more broadly for learning statistical models with sparse structure. In the context of learning directed acyclic graphs, greedy algorithms are popular despite…

Machine Learning · Computer Science 2021-11-01 Goutham Rajendran , Bohdan Kivva , Ming Gao , Bryon Aragam