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We study statistical problems, such as planted clique, its variants, and sparse principal component analysis in the context of average-case communication complexity. Our motivation is to understand the statistical-computational trade-offs…

Computational Complexity · Computer Science 2021-07-06 Cyrus Rashtchian , David P. Woodruff , Peng Ye , Hanlin Zhu

In this review, we present the encounter-based approach to target search problems, in which the diffusive dynamics is described by the joint probability of the position of the particle and the number of its encounters with a given target…

Statistical Mechanics · Physics 2025-07-16 Denis S. Grebenkov

We analyze the problem of learning a single user's preferences in an active learning setting, sequentially and adaptively querying the user over a finite time horizon. Learning is conducted via choice-based queries, where the user selects…

Machine Learning · Statistics 2017-02-27 Stephen N. Pallone , Peter I. Frazier , Shane G. Henderson

A method of analyzing time bounds for randomized distributed algorithms is presented, in the context of a new and general framework for describing and reasoning about randomized algorithms. The method consists of proving auxiliary…

Combinatorics · Mathematics 2016-09-06 Nancy Lynch , Isaac Saias , Roberto Segala

We introduce a formalism based on a continuous time approximation, to study the characteristics of Page Rank random walks. We find that the diffusion of the occupancy probability has a dynamics that exponentially "forgets" the initial…

Statistical Mechanics · Physics 2020-07-17 Emilio Aced Fuentes , Simone Santini

The asynchronous rumor algorithm spreading propagates a piece of information, the so-called rumor, in a network. Starting with a single informed node, each node is associated with an exponential time clock with rate $1$ and calls a random…

Data Structures and Algorithms · Computer Science 2020-05-19 Ali Pourmiri , Bernard Mans

We address the problem of searching for a change point in an anomalous process among a finite set of M processes. Specifically, we address a composite hypothesis model in which each process generates measurements following a common…

Machine Learning · Statistics 2024-12-30 Liad Lea Didi , Tomer Gafni , Kobi Cohen

An agent acquires information dynamically until her belief about a binary state reaches an upper or lower threshold. She can choose any signal process subject to a constraint on the rate of entropy reduction. Strategies are ordered by "time…

Theoretical Economics · Economics 2024-08-23 Daniel Chen , Weijie Zhong

In this paper, we study a problem of detecting the source of diffused information by querying individuals, given a sample snapshot of the information diffusion graph, where two queries are asked: {\em (i)} whether the respondent is the…

Social and Information Networks · Computer Science 2020-10-23 Jaeyoung Choi , Sangwoo Moon , Jiin Woo , Kyunghwan Son , Jinwoo Shin , Yung Yi

We study the worst-case communication complexity of distributed algorithms computing a path problem based on stationary distributions of random walks in a network $G$ with the caveat that $G$ is also the communication network. The problem…

Data Structures and Algorithms · Computer Science 2008-10-30 Rahul Sami , Andy Twigg

Consider a stochastic search model with resetting for an unknown stationary target $a\in\mathbb{R}$ with known distribution $\mu$. The searcher begins at the origin and performs Brownian motion with diffusion constant $D$. The searcher is…

Probability · Mathematics 2018-12-04 Ross G. Pinsky

We consider optimal stopping problems, in which a sequence of independent random variables is drawn from a known continuous density. The objective of such problems is to find a procedure which maximizes the expected reward; this is often…

Probability · Mathematics 2020-12-07 Hugh Entwistle , Christopher Lustri , Georgy Sofronov

We obtain distribution-free bounds for various fundamental quantities used in probability theory by solving optimization problems that search for extreme distributions among all distributions with the same mean and dispersion. These…

Optimization and Control · Mathematics 2024-09-27 Pieter Kleer , Johan S. H. van Leeuwaarden , Bas Verseveldt

We study the search kinetics of an immobile target by a concentration of randomly moving searchers. The object of the study is to optimize the probability of detection within the constraints of our model. The target is hidden on a…

Statistical Mechanics · Physics 2009-11-11 G. Oshanin , H. S. Wio , K. Lindenberg , S. F. Burlatsky

Multi-mode resource-constrained project scheduling problems (MRCPSPs) are classified as NP-hard problems, in which a task has different execution modes characterized by different resource requirements. Estimation of distribution algorithm…

Other Computer Science · Computer Science 2014-02-25 Omar S. Soliman , Elshimaa A. R. Elgendi

We consider the problem of trajectory planning in an environment comprised of a set of obstacles with uncertain locations. While previous approaches model the uncertainties with a prescribed Gaussian distribution, we consider the realistic…

Systems and Control · Computer Science 2021-01-12 Vasileios Lefkopoulos , Maryam Kamgarpour

This work considers the problem of the noisy binary search in a sorted array. The noise is modeled by a parameter $p$ that dictates that a comparison can be incorrect with probability $p$, independently of other queries. We state two types…

Data Structures and Algorithms · Computer Science 2025-02-27 Dariusz Dereniowski , Aleksander Łukasiewicz , Przemysław Uznański

We consider the average-consensus problem in a multi-node network of finite size. Communication between nodes is modeled by a sequence of directed signals with arbitrary communication delays. Four distributed algorithms that achieve…

Distributed, Parallel, and Cluster Computing · Computer Science 2011-06-23 Kevin Topley , Vikram Krishnamurthy

We study the classic problem in which a Searcher must locate a hidden point, also called the Hider in a network, starting from a root point. The network may be either bounded or unbounded, thus generalizing well-known settings such as…

Optimization and Control · Mathematics 2019-08-07 Spyros Angelopoulos , Thomas Lidbetter

By embedding uncertainty into time, we obtain a conjoint axiomatic characterization of both Exponential Discounting and Subjective Expected Utility that accommodates arbitrary state and outcome spaces. In doing so, we provide a novel and…

Theoretical Economics · Economics 2024-03-25 Lorenzo Bastianello , Vassili Vergopoulos
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