English
Related papers

Related papers: Corners in Quasirandom Groups via Sparse Mixing

200 papers

Let $P(t),Q(t)\in \mathbb{Q}(t)$ be rational functions such that $P(t),Q(t)$ and the constant function $1$ are linearly independent over $\mathbb{Q}$, we prove an asymptotic formula for the number of the corner configurations…

Number Theory · Mathematics 2025-01-10 Zi Li Lim

We prove a quantitative Roth-type theorem for polynomial corners in $\mathbb{R}^2$. Let $P_1$ and $P_2$ be two linearly independent polynomials with zero constant term. We show that any measurable subset of $[0,1]^2$ with positive measure…

Classical Analysis and ODEs · Mathematics 2023-07-04 Xuezhi Chen , Jingwei Guo

The quasi-redirecting (QR) boundary, introduced by Qing and Rafi, generalizes the Gromov boundary for studying the large-scale geometry of finitely generated groups. Although it is not known to exist for all such groups, its existence has…

Group Theory · Mathematics 2025-05-13 Hoang Thanh Nguyen

Corner trees, introduced in "Even-Zohar and Leng, 2021, Proceedings of the 2021 ACM-SIAM Symposium on Discrete Algorithms", allow for the efficient counting of certain permutation patterns. Here we identify corner trees as a subset of…

Combinatorics · Mathematics 2025-05-12 Joscha Diehl , Emanuele Verri

We study the rank of complex sparse matrices in which the supports of different columns have small intersections. The rank of these matrices, called design matrices, was the focus of a recent work by Barak et. al. (BDWY11) in which they…

Combinatorics · Mathematics 2012-11-05 Zeev Dvir , Shubhangi Saraf , Avi Wigderson

The ExactlyN problem in the number-on-forehead (NOF) communication setting asks $k$ players, each of whom can see every input but their own, if the $k$ input numbers add up to $N$. Introduced by Chandra, Furst and Lipton in 1983, ExactlyN…

Computational Complexity · Computer Science 2023-09-14 Lianna Hambardzumyan , Toniann Pitassi , Suhail Sherif , Morgan Shirley , Adi Shraibman

The k-means algorithm is a well-known method for partitioning n points that lie in the d-dimensional space into k clusters. Its main features are simplicity and speed in practice. Theoretically, however, the best known upper bound on its…

Computational Geometry · Computer Science 2008-12-03 Andrea Vattani

We extend the theory of fast Fourier transforms on finite groups to finite inverse semigroups. We use a general method for constructing the irreducible representations of a finite inverse semigroup to reduce the problem of computing its…

Group Theory · Mathematics 2011-08-02 Martin Malandro

Network coordination - synchronising traffic signals, scheduling trains, assigning communication slots requires minimising pairwise costs across coupled systems. These problems are NP-hard yet share a common Fourier-sparse structure…

Quantum Physics · Physics 2026-03-10 Vinayak Dixit

We consider the problem of improving the efficiency of randomized Fourier feature maps to accelerate training and testing speed of kernel methods on large datasets. These approximate feature maps arise as Monte Carlo approximations to…

Machine Learning · Statistics 2015-08-11 Haim Avron , Vikas Sindhwani , Jiyan Yang , Michael Mahoney

We introduce the notion of "quasi-symmetric" polynomials, which is a generalization of the notion of symmetry, and is particularly suited to the setting of polynomial rings over finite fields. The properties of this new class of functions…

Number Theory · Mathematics 2007-05-23 Vinay Deolalikar

Although real-world complex systems typically interact through sparse and heterogeneous networks, analytic solutions of their dynamics are limited to models with all-to-all interactions. Here, we solve the dynamics of a broad range of…

Disordered Systems and Neural Networks · Physics 2025-01-28 Fernando L. Metz

We present a new approach to study measures on ensembles of contours, polymers or other objects interacting by some sort of exclusion condition. For concreteness we develop it here for the case of Peierls contours. Unlike existing methods,…

Probability · Mathematics 2016-08-15 Roberto Fernández , Pablo A. Ferrari , Nancy L. Garcia

For a prime $p$ and a polynomial $F(X,Y)$ over a finite field $\mathbb{F}_p$ of $p$ elements, we give upper bounds on the number of solutions $$ F(x,y)=0, \quad x\in\mathcal{A}, \ y\in \mathcal{B}, $$ where $\mathcal{A}$ and $\mathcal{B}$…

Number Theory · Mathematics 2018-03-07 László Mérai , Igor E. Shparlinski

We establish a class of sufficient conditions, ensuring that a sequence of multiple integrals with respect to a free Poisson measure converges to a semicircular limit. We use this result to construct a set of explicit counterexamples,…

Operator Algebras · Mathematics 2014-09-05 Solesne Bourguin , Giovanni Peccati

We investigate the asymptotic behavior of the empirical eigenvalues distribution of the partial transpose of a random quantum state. The limiting distribution was previously investigated via Wishart random matrices indirectly (by…

Mathematical Physics · Physics 2013-07-16 Motohisa Fukuda , Piotr Śniady

In this thesis, we investigate the asymptotics of random partitions chosen according to probability measures coming from the representation theory of the symmetric groups $S_n$ and of the finite Chevalley groups $GL(n,F_q)$ and…

Representation Theory · Mathematics 2010-12-21 Pierre-Loïc Méliot

We study the computational phase transition in a multi-frequency group synchronization problem, where pairwise relative measurements of group elements are observed across multiple frequency channels and corrupted by Gaussian noise. Using…

Statistics Theory · Mathematics 2026-01-29 Zhangsong Li

Given a set of points, clustering consists of finding a partition of a point set into $k$ clusters such that the center to which a point is assigned is as close as possible. Most commonly, centers are points themselves, which leads to the…

Machine Learning · Computer Science 2023-10-16 Maria Sofia Bucarelli , Matilde Fjeldsø Larsen , Chris Schwiegelshohn , Mads Bech Toftrup

We consider high-dimensional distribution estimation through autoregressive networks. By combining the concepts of sparsity, mixtures and parameter sharing we obtain a simple model which is fast to train and which achieves state-of-the-art…

Machine Learning · Statistics 2016-04-28 Marc Goessling , Yali Amit
‹ Prev 1 3 4 5 6 7 10 Next ›