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There has been a long-standing interest in computing diverse solutions to optimization problems. Motivated by reallocation of governmental institutions in Sweden, in 1995 J. Krarup posed the problem of finding $k$ edge-disjoint Hamiltonian…

Data Structures and Algorithms · Computer Science 2022-02-22 Jie Gao , Mayank Goswami , Karthik C. S. , Meng-Tsung Tsai , Shih-Yu Tsai , Hao-Tsung Yang

Local graph clustering and the closely related seed set expansion problem are primitives on graphs that are central to a wide range of analytic and learning tasks such as local clustering, community detection, nodes ranking and feature…

Machine Learning · Computer Science 2020-07-21 Kimon Fountoulakis , Di Wang , Shenghao Yang

We examine the concentration of uniform generalization errors around their expectation in binary linear classification problems via an isoperimetric argument. In particular, we establish Poincar\'{e} and log-Sobolev inequalities for the…

Machine Learning · Statistics 2025-06-27 Shogo Nakakita

In a classical optimal stopping problem the aim is to maximize the expected value of a functional of a diffusion evaluated at a stopping time. This note considers optimal stopping problems beyond this paradigm. We study problems in which…

Probability · Mathematics 2017-08-04 Vicky Henderson , David Hobson , Matthew Zeng

Consider a set $P$ of $n$ points picked uniformly and independently from $[0,1]^d$ for a constant dimension $d$ -- such a point set is extremely well behaved in many aspects. For example, for a fixed $r \in [0,1]$, we prove a new…

Computational Geometry · Computer Science 2023-11-01 Sariel Har-Peled , Elfarouk Harb

In this work, we consider an optimal control problem subject to a nonlinear PDE constraint and apply it to the regularized $p$-Laplace equation. To this end, a reduced unconstrained optimization problem in terms of the control variable is…

Numerical Analysis · Mathematics 2020-06-29 Bernhard Endtmayer , Ulrich Langer , Ira Neitzel , Winnifried Wollner , Thomas Wick

In this paper, we study a retailer price optimization problem which includes the practical constraints: maximum number of price changes and minimum amount of price change (if a change is recommended). We provide a closed-form formula for…

Optimization and Control · Mathematics 2021-04-21 Xiaojie Wang , Hsin-Chan Huang , Lanshan Han , Alvin Lim

We are studying $d$-dimensional geometric problems that have algorithms with $1-1/d$ appearing in the exponent of the running time, for example, in the form of $2^{n^{1-1/d}}$ or $n^{k^{1-1/d}}$. This means that these algorithms perform…

Data Structures and Algorithms · Computer Science 2016-12-06 Dániel Marx , Anastasios Sidiropoulos

We give a probabilistic analysis of the unit-demand Euclidean capacitated vehicle routing problem in the random setting, where the input distribution consists of $n$ unit-demand customers modeled as independent, identically distributed…

Data Structures and Algorithms · Computer Science 2021-12-14 Claire Mathieu , Hang Zhou

We study the problem of searching for a target at some unknown location in $\mathbb{R}^d$ when additional information regarding the position of the target is available in the form of predictions. In our setting, predictions come as…

Computational Geometry · Computer Science 2025-04-08 Sergio Cabello , Panos Giannopoulos

We propose a new approach for the study of the quadratic stochastic Euclidean bipartite matching problem between two sets of $N$ points each, $N\gg 1$. The points are supposed independently randomly generated on a domain…

Statistical Mechanics · Physics 2015-12-02 Sergio Caracciolo , Gabriele Sicuro

The work studies the problem of decentralized constrained POMDPs in a team-setting where multiple nonstrategic agents have asymmetric information. Using an extension of Sion's Minimax theorem for functions with positive infinity and results…

Optimization and Control · Mathematics 2025-04-29 Nouman Khan , Vijay Subramanian

We develop value iteration-based algorithms to solve in a unified manner different classes of combinatorial zero-sum games with mean-payoff type rewards. These algorithms rely on an oracle, evaluating the dynamic programming operator up to…

Computer Science and Game Theory · Computer Science 2024-11-12 Xavier Allamigeon , Stéphane Gaubert , Ricardo D. Katz , Mateusz Skomra

We prove optimal quantitative estimates on the first-order correctors on supercritical percolation clusters: we show that they are bounded in $d\geq 3$ and have logarithmic growth in $d = 2$, in the sense of stretched exponential moments.…

Probability · Mathematics 2020-05-15 Paul Dario

This paper studies finite-time optimal consumption-investment problems with power, logarithmic and exponential utilities, in a regime switching market with random coefficients, subject to coupled constraints on the consumption and…

Probability · Mathematics 2022-11-11 Ying Hu , Xiaomin Shi , Zuo Quan Xu

In this paper, we analyze the convergence of a distributed Robbins-Monro algorithm for both constrained and unconstrained optimization in multi-agent systems. The algorithm searches for local minima of a (nonconvex) objective function which…

Information Theory · Computer Science 2011-04-20 Pascal Bianchi , Jérémie Jakubowicz

Consider the problem of finding a point in a unit $n$-dimensional $\ell_p$-ball ($p\ge 2$) such that the minimum of the weighted Euclidean distance from given $m$ points is maximized. We show in this paper that the recent…

Optimization and Control · Mathematics 2016-06-22 Zuping Wu , Yong Xia , Shu Wang

The classical Erd\H{o}s-Littlewood-Offord problem concerns the random variable $X = a_1 \xi_1 + \dots + a_n \xi_n$, where $a_i \in \mathbb{R} \setminus \{0\}$ are fixed and $\xi_i \sim \text{Ber}(1/2)$ are independent. The…

Combinatorics · Mathematics 2020-01-03 Mihir Singhal

We consider the problem of estimating the possibly non-convex cost of an agent by observing its interactions with a nonlinear, non-stationary and stochastic environment. For this inverse problem, we give a result that allows to estimate the…

Optimization and Control · Mathematics 2023-07-24 Émiland Garrabé , Hozefa Jesawada , Carmen Del Vecchio , Giovanni Russo

We investigate a class of chance-constrained combinatorial optimization problems. Given a pre-specified risk level $\epsilon \in [0,1]$, the chance-constrained program aims to find the minimum cost selection of a vector of binary decisions…

Optimization and Control · Mathematics 2020-06-02 Hao-Hsiang Wu , Simge Kucukyavuz
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