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Two sets of objects of size $n$ are to be matched to each other based on i.i.d. costs associated to every pair of objects. Objects prefer to be matched as cheaply as possible, and a matching is said to be stable if there is no pair of…

Probability · Mathematics 2025-10-28 Daniel Ahlberg , Maria Deijfen , Tiffany Y. Y. Lo

We consider in this paper the collection of near maxima of the discrete, two dimensional Gaussian free field in a box with Dirichlet boundary conditions. We provide a rough description of the geometry of the set of near maxima, estimates on…

Probability · Mathematics 2013-04-09 Jian Ding , Ofer Zeitouni

We study the maximum of the random assignment process on rectangular matrices. We derive first-order asymptotics for the expected maximum, prove a law of large numbers under mild tail assumptions, and obtain exponential upper bounds for the…

Probability · Mathematics 2025-09-23 Timofey Moskalenko

Gaussian random processes which variances reach theirs maximum values at unique points are considered. Exact asymptotic behaviors of probabilities of large absolute maximums of theirs trajectories have been evaluated using Double Sum Method…

Probability · Mathematics 2019-01-29 E. Hashorva , S. Kobelkov , V. I. Piterbarg

We study distributed estimation of a Gaussian mean under communication constraints in a decision theoretical framework. Minimax rates of convergence, which characterize the tradeoff between the communication costs and statistical accuracy,…

Statistics Theory · Mathematics 2020-02-11 T. Tony Cai , Hongji Wei

We study high-dimensional stochastic optimal control problems in which many agents cooperate to minimize a convex cost functional. We consider both the full-information problem, in which each agent observes the states of all other agents,…

Probability · Mathematics 2023-01-10 Joe Jackson , Daniel Lacker

We continue the study of the assignment problem for a random cost matrix. We analyse the number of $k$-cycles for the solution and their dependence on the symmetry of the random matrix. We observe that for a symmetric matrix one and…

Discrete Mathematics · Computer Science 2009-11-13 J. G. Esteve , Fernando Falceto

In this paper, we study a random field constructed from the two-dimensional Gaussian free field (GFF) by modifying the variance along the scales in the neighborhood of each point. The construction can be seen as a local martingale transform…

Probability · Mathematics 2022-05-25 Louis-Pierre Arguin , Frédéric Ouimet

In this paper, we consider the problem of Gaussian approximation for the online linear regression task. We derive the corresponding rates for the setting of a constant learning rate and study the explicit dependence of the convergence rate…

Machine Learning · Statistics 2025-09-18 Marat Khusainov , Marina Sheshukova , Alain Durmus , Sergey Samsonov

The principal results of this contribution are the weak and strong limits of maxima of contracted stationary Gaussian random sequences. Due to the random contraction we introduce a modified Berman condition which is sufficient for the weak…

Probability · Mathematics 2013-12-10 Enkelejd Hashorva , Zhichao Weng

Recently in Gao and Stoev (2018) it was established that the concentration of maxima phenomenon is the key to solving the exact sparse support recovery problem in high dimensions. This phenomenon, known also as relative stability, has been…

Statistics Theory · Mathematics 2020-05-05 Rafail Kartsioukas , Zheng Gao , Stilian Stoev

We show that the rescaled maximum of the discrete Gaussian Free Field (DGFF) in dimension larger or equal to 3 is in the maximal domain of attraction of the Gumbel distribution. The result holds both for the infinite-volume field as well as…

Probability · Mathematics 2016-04-05 Alberto Chiarini , Alessandra Cipriani , Rajat Subhra Hazra

We give a necessary and sufficient condition for symmetric infinitely divisible distribution to have Gaussian component. The result can be applied to approximation the distribution of finite sums of random variables. Particularly, it shows…

Probability · Mathematics 2015-08-25 Lev B. Klebanov , Irina V. Volchenkova , Ashot V. Kakosyan

We estimate the global minimum variance (GMV) portfolio in the high-dimensional case using results from random matrix theory. This approach leads to a shrinkage-type estimator which is distribution-free and it is optimal in the sense of…

Statistical Finance · Quantitative Finance 2023-04-19 Taras Bodnar , Nestor Parolya , Wolfgang Schmid

We derive a Gaussian approximation result for the maximum of a sum of high-dimensional random vectors. Specifically, we establish conditions under which the distribution of the maximum is approximated by that of the maximum of a sum of the…

Statistics Theory · Mathematics 2018-01-24 Victor Chernozhukov , Denis Chetverikov , Kengo Kato

In the spirit of [M. Biskup & O. Louidor, Adv. Math. 330 (2018)], we study the local structure of $\star$-scale invariant fields -- a class of log-correlated Gaussian fields -- around their extremal points by characterising the law of the…

Probability · Mathematics 2026-05-01 Federico Bertacco , Martin Hairer

Suppose $k$ centers are fit to $m$ points by heuristically minimizing the $k$-means cost; what is the corresponding fit over the source distribution? This question is resolved here for distributions with $p\geq 4$ bounded moments; in…

Machine Learning · Computer Science 2013-11-11 Matus Telgarsky , Sanjoy Dasgupta

We consider continuous time random interlacements on $\mathbb{Z}^d$, $d \ge 3$, and characterize the distribution of the corresponding stationary random field of occupation times. When d = 3, we relate this random field to the…

Probability · Mathematics 2012-10-30 Alain-Sol Sznitman

Many inference problems involving questions of optimality ask for the maximum or the minimum of a finite set of unknown quantities. This technical report derives the first two posterior moments of the maximum of two correlated Gaussian…

Machine Learning · Statistics 2009-10-02 Philipp Hennig

We investigate the sub-Gaussian property for almost surely bounded random variables. If sub-Gaussianity per se is de facto ensured by the bounded support of said random variables, then exciting research avenues remain open. Among these…

Probability · Mathematics 2019-07-16 Julyan Arbel , Olivier Marchal , Hien D. Nguyen