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In recent years, large language models (LLMs) have demonstrated remarkable capabilities in comprehending and generating natural language content, attracting widespread attention in both industry and academia. An increasing number of…

Databases · Computer Science 2026-01-08 Keke Huang , Yimin Shi , Dujian Ding , Yifei Li , Yang Fei , Laks Lakshmanan , Xiaokui Xiao

We explore a multiple-stage variant of the min-max robust selection problem with budgeted uncertainty that includes queries. First, one queries a subset of items and gets the exact values of their uncertain parameters. Given this…

Optimization and Control · Mathematics 2025-01-07 Xiaoyu Chen , Marc Goerigk , Michael Poss

We introduce a framework to identify Fluctuation Relations for vector-valued observables in physical systems evolving through a stochastic dynamics. These relations arise from the particular structure of a suitable entropic functional and…

Statistical Mechanics · Physics 2025-10-22 Raphael Chetrite , Stefano Marcantoni

These notes are devoted to fluctuations of one-dimensional random walks. We discuss various approaches to first-passage times and to the corresponding conditional distributions. After discussion of some classical methods, such as reflection…

Probability · Mathematics 2026-02-23 Denis Denisov , Vitali Wachtel

This PhD thesis is organized as follows. In the first two chapters I will review some basic notions of statistical physics of disordered systems, such as random graph theory, the mean-field approximation, spin glasses and combinatorial…

Disordered Systems and Neural Networks · Physics 2019-10-15 Enrico M. Malatesta

Consider a polynomial optimisation problem, whose instances vary continuously over time. We propose to use a coordinate-descent algorithm for solving such time-varying optimisation problems. In particular, we focus on relaxations of…

Optimization and Control · Mathematics 2019-09-24 Jie Liu , Jakub Marecek , Andrea Simonetto , Martin Takac

The common way to optimize auction and pricing systems is to set aside a small fraction of the traffic to run experiments. This leads to the question: how can we learn the most with the smallest amount of data? For truthful auctions, this…

Computer Science and Game Theory · Computer Science 2021-11-09 Renato Paes Leme , Balasubramanian Sivan , Yifeng Teng , Pratik Worah

The typical behavior of optimal solutions to portfolio optimization problems with absolute deviation and expected shortfall models using replica analysis was pioneeringly estimated by S. Ciliberti and M. M\'ezard [Eur. Phys. B. 57, 175…

Portfolio Management · Quantitative Finance 2016-12-15 Takashi Shinzato , Muneki Yasuda

This paper presents an in-depth mathematical analysis of the Monte Carlo replica method, commonly used in global fitting studies within the high-energy physics theory field. For the first time, we offer a rigorous derivation of the…

High Energy Physics - Phenomenology · Physics 2024-10-10 Mark N. Costantini

Modern stochastic optimization methods often rely on uniform sampling which is agnostic to the underlying characteristics of the data. This might degrade the convergence by yielding estimates that suffer from a high variance. A possible…

Machine Learning · Statistics 2018-06-07 Zalán Borsos , Andreas Krause , Kfir Y. Levy

A Gaussian fluctuation formula is proved for linear statistics of complex random matrices in the case that the statistic is rotationally invariant. For a general linear statistic without this symmetry, Coulomb gas theory is used to predict…

Statistical Mechanics · Physics 2007-05-23 P. J. Forrester

We consider the Random Euclidean Assignment Problem in dimension $d=1$, with linear cost function. In this version of the problem, in general, there is a large degeneracy of the ground state, i.e. there are many different optimal matchings…

Probability · Mathematics 2021-07-16 Sergio Caracciolo , Vittorio Erba , Andrea Sportiello

We present a comparative study of several algorithms for an in-plane random walk with a variable step. The goal is to check the efficiency of the algorithm in the case where the random walk terminates at some boundary. We recently found…

Statistical Mechanics · Physics 2019-04-17 Olga Klimenkova , Anton Yu. Menshutin , Lev N. Shchur

Numerical computing of the rank of a matrix is a fundamental problem in scientific computation. The datasets generated by the internet often correspond to the analysis of high-dimensional sparse matrices. Notwithstanding recent advances in…

Numerical Analysis · Mathematics 2023-04-13 Chen Zhao , Yuqing Liu , Li Hu , Zhengzhong Yuan

The ``Brownian bees'' model describes an ensemble of $N=$~const independent branching Brownian particles. The conservation of $N$ is provided by a modified branching process. When a particle branches into two particles, the particle which…

Statistical Mechanics · Physics 2023-02-08 Pavel Sasorov , Arkady Vilenkin , Naftali R. Smith

In systems of diffusing particles, we investigate large deviations of a time-averaged measure of clustering around one particle. We focus on biased ensembles of trajectories, which realise large-deviation events. The bias acts on a single…

Statistical Mechanics · Physics 2021-06-02 Jakub Dolezal , Robert L. Jack

We introduce a numerical procedure to evaluate directly the probabilities of large deviations of physical quantities, such as current or density, that are local in time. The large-deviation functions are given in terms of the typical…

Statistical Mechanics · Physics 2009-11-11 Cristian Giardina' , Jorge Kurchan , Luca Peliti

Fluctuation scaling is observed phenomenon from complex networks through finance to ecology. It means that the variance and the mean of a specific quantity are related as $\ev{\sigma^2|n}\propto \ev{n|A}^{2\alpha}$ with $1/2\geq \alpha \geq…

Physics and Society · Physics 2008-12-02 Zoltan Eisler , Janos Kertesz

A large deviation principle is established for a general class of stochastic flows in the small noise limit. This result is then applied to a Bayesian formulation of an image matching problem, and an approximate maximum likelihood property…

Statistics Theory · Mathematics 2010-02-24 Amarjit Budhiraja , Paul Dupuis , Vasileios Maroulas

We consider a discrete-time random walk on a one-dimensional lattice with space and time-dependent random jump probabilities, known as the Beta random walk. We are interested in the probability that, for a given realization of the jump…

Statistical Mechanics · Physics 2023-07-28 Alexander K. Hartmann , Alexandre Krajenbrink , Pierre Le Doussal