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Large-scale nonsmooth optimization problems arise in many real-world applications, but obtaining exact function and subgradient values for these problems may be computationally expensive or even infeasible. In many practical settings, only…

Optimization and Control · Mathematics 2026-04-10 Jenni Lampainen , Kaisa Joki , Napsu Karmitsa , Marko M. Mäkelä

This paper investigates the asymptotics of the maximal throughput of communication over AWGN channels by $n$ channel uses under a covert constraint in terms of an upper bound $\delta$ of Kullback-Leibler divergence (KL divergence). It is…

Information Theory · Computer Science 2026-04-08 Xinchun Yu , Shuangqing Wei , Shao-Lun Huang , Xiao-Ping Zhang

From the output produced by a memoryless deletion channel from a uniformly random input of known length $n$, one obtains a posterior distribution on the channel input. The difference between the Shannon entropy of this distribution and that…

Information Theory · Computer Science 2018-08-01 Arash Atashpendar , David Mestel , A. W. Roscoe , Peter Y. A. Ryan

We report the results of exact diagonalization studies of Hubbard models on a $4\times 4$ square lattice with periodic boundary conditions and various degrees and patterns of inhomogeneity, which are represented by inequivalent hopping…

Superconductivity · Physics 2009-11-13 Wei-Feng Tsai , Hong Yao , Andreas Laeuchli , Steven A. Kivelson

Inspired by the boolean discrepancy problem, we study the following optimization problem which we term \textsc{Spherical Discrepancy}: given $m$ unit vectors $v_1, \dots, v_m$, find another unit vector $x$ that minimizes $\max_i \langle x,…

Computational Complexity · Computer Science 2019-11-19 Chris Jones , Matt McPartlon

We present a results about convergence of products of row-stochastic matrices which are infinite to the left and all have positive diagonals. This is regarded as in inhomogeneous consensus process where confidence weights may change in…

Optimization and Control · Mathematics 2007-05-23 Jan Lorenz

We prove an exponential decay concentration inequality to bound the tail probability of the difference between the log-likelihood of discrete random variables on a finite alphabet and the negative entropy. The concentration bound we derive…

Probability · Mathematics 2021-06-23 Yunpeng Zhao

The centralized circumcentered-reflection method (\cCRM) of~\cite{Behling:2024} converges superlinearly to a solution of $\operatorname{find}\;z\in X\cap Y$ when $\inte(X\cap Y)\neq\emptyset$ and the boundaries of $X$ and $Y$ are…

Optimization and Control · Mathematics 2026-04-14 Yunier Bello-Cruz

In this paper, we study the inverse scattering problem for a class of signals that have a compactly supported reflection coefficient. The problem boils down to the solution of the Gelfand-Levitan-Marchenko (GLM) integral equations with a…

Computational Physics · Physics 2019-02-12 Vishal Vaibhav

We derive sharp upper and lower bounds for the pointwise concentration function of the maximum statistic of $d$ identically distributed real-valued random variables. Our first main result places no restrictions either on the common marginal…

Statistics Theory · Mathematics 2025-08-04 Matias D. Cattaneo , Ricardo P. Masini , William G. Underwood

We prove concentration bounds for the following classes of quantum states: (i) output states of shallow quantum circuits, answering an open question from [DPMRF22]; (ii) injective matrix product states; (iii) output states of dense…

Quantum Physics · Physics 2023-05-17 Anurag Anshu , Tony Metger

We show that for constraint satisfaction problems (CSPs), sub-exponential size linear programming relaxations are as powerful as $n^{\Omega(1)}$-rounds of the Sherali-Adams linear programming hierarchy. As a corollary, we obtain…

Computational Complexity · Computer Science 2018-01-03 Pravesh K. Kothari , Raghu Meka , Prasad Raghavendra

The bandwidth of a graph is the labeling of vertices with minimum maximum edge difference. For many graph families this is NP-complete. A classic result computes the bandwidth for the hypercube. We generalize this result to give sharp lower…

Discrete Mathematics · Computer Science 2007-05-23 Tanya Y. Berger-Wolf , Mitchell A. Harris

In this note we present a construction which improves the best known bound on the minimal dispersion of large volume boxes in the unit cube. Let $d>1$. The dispersion of $T \subset [0,1]^d$ is defined as the supremum of the volume taken…

Metric Geometry · Mathematics 2022-01-13 Kurt S. MacKay

We establish that unitarity of scattering amplitudes imposes universal entropy bounds. The maximal entropy of a self-sustained quantum field object of radius R is equal to its surface area and at the same time to the inverse running…

High Energy Physics - Theory · Physics 2021-03-31 Gia Dvali

We study the decentralized consensus and stochastic optimization problems with compressed communications over static directed graphs. We propose an iterative gradient-based algorithm that compresses messages according to a desired…

Optimization and Control · Mathematics 2022-04-19 Mohammad Taha Toghani , César A. Uribe

Non-orthogonal communication is a promising technique for future wireless networks (e.g., 6G and Wi-Fi 7). In the vector channel model, designing efficient non-orthogonal communication schemes amounts to the following extremum problem: \[…

Metric Geometry · Mathematics 2021-05-11 Gergely Ambrus , Bo Bai , Jianfeng Hou

For integers $n$ and $k$, the density Hales-Jewett number $c_{n,k}$ is defined as the maximal size of a subset of $[k]^n$ that contains no combinatorial line. We show that for $k \ge 3$ the density Hales-Jewett number $c_{n,k}$ is equal to…

Computational Complexity · Computer Science 2018-07-03 Adi Shraibman

We initiate a study of the following problem: Given a continuous domain $\Omega$ along with its convex hull $\mathcal{K}$, a point $A \in \mathcal{K}$ and a prior measure $\mu$ on $\Omega$, find the probability density over $\Omega$ whose…

Data Structures and Algorithms · Computer Science 2020-04-17 Jonathan Leake , Nisheeth K. Vishnoi

In this note, we show that the relative entropy of an empirical distribution of $n$ samples drawn from a set of size $k$ with respect to the true underlying distribution is exponentially concentrated around its expectation, with central…

Statistics Theory · Mathematics 2022-03-03 Rohit Agrawal
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