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We revisit the online Unit Covering problem in higher dimensions: Given a set of $n$ points in $\mathbb{R}^d$, that arrive one by one, cover the points by balls of unit radius, so as to minimize the number of balls used. In this paper, we…

Computational Geometry · Computer Science 2018-08-29 Adrian Dumitrescu , Anirban Ghosh , Csaba D. Tóth

We investigate the evolutionary dynamics in directed and/or weighted networks. We study the fixation probability of a mutant in finite populations in stochastic voter-type dynamics for several update rules. The fixation probability is…

Physics and Society · Physics 2009-03-12 Naoki Masuda , Hisashi Ohtsuki

We study the online preemptive scheduling of intervals and jobs (with restarts). Each interval or job has an arrival time, a deadline, a length and a weight. The objective is to maximize the total weight of completed intervals or jobs.…

Data Structures and Algorithms · Computer Science 2012-04-16 Stanley P. Y. Fung , Chung Keung Poon , Feifeng Zheng

This paper studies an online cost optimization problem for distributed storage and access. The goal is to dynamically create and delete copies of data objects over time at geo-distributed servers to serve access requests and minimize the…

Data Structures and Algorithms · Computer Science 2025-10-29 Tianyu Zuo , Xueyan Tang , Bu Sung Lee , Jianfei Cai

Optimizing over the stationary distribution of stochastic differential equations (SDEs) is computationally challenging. A new forward propagation algorithm has been recently proposed for the online optimization of SDEs. The algorithm solves…

Probability · Mathematics 2022-07-12 Ziheng Wang , Justin Sirignano

One of the fundamental problems in distributed computing is how to efficiently perform routing in a faulty network in which each link fails with some probability. This paper investigates how big the failure probability can be, before the…

Probability · Mathematics 2007-05-23 Omer Angel , Itai Benjamini , Eran Ofek , Udi Wieder

In view of the fact that routing algorithms are network layer entities and the varying performance of any routing algorithm depends on the underlying networks. Localized routing algorithms avoid the problems associated with the maintenance…

Networking and Internet Architecture · Computer Science 2011-03-18 Abdulbaset H. Mohammad

Can one choose a good Huffman code on the fly, without knowing the underlying distribution? Online Slot Allocation (OSA) models this and similar problems: There are n slots, each with a known cost. There are n items. Requests for items are…

Data Structures and Algorithms · Computer Science 2013-10-09 Monik Khare , Claire Mathieu , Neal E. Young

In this work, we develop a distributed source routing algorithm for topology discovery suitable for ISP transport networks, that is however inspired by opportunistic algorithms used in ad hoc wireless networks. We propose a plug-and-play…

Networking and Internet Architecture · Computer Science 2011-05-02 Christophe Betoule , Thomas Bonald , Remi Clavier , Dario Rossi , Giuseppe Rossini , Gilles Thouenon

In this paper, the problem of distributed optimization is studied via a network of agents. Each agent only has access to a stochastic gradient of its own objective function in the previous time, and can communicate with its neighbors via a…

Optimization and Control · Mathematics 2024-01-29 Yuchen Yang , Kaihong Lu , Long Wang

The knapsack problem is one of the classical problems in combinatorial optimization: Given a set of items, each specified by its size and profit, the goal is to find a maximum profit packing into a knapsack of bounded capacity. In the…

Data Structures and Algorithms · Computer Science 2020-12-02 Susanne Albers , Arindam Khan , Leon Ladewig

In evaluating an algorithm, worst-case analysis can be overly pessimistic. Average-case analysis can be overly optimistic. An intermediate approach is to show that an algorithm does well on a broad class of input distributions. Koutsoupias…

Data Structures and Algorithms · Computer Science 2015-06-02 Neal E. Young

High dimensional piecewise stationary graphical models represent a versatile class for modelling time varying networks arising in diverse application areas, including biology, economics, and social sciences. There has been recent work in…

Machine Learning · Statistics 2018-06-21 Hossein Keshavarz , George Michailidis , Yves Atchade

For a sensor network, a tractable spatially-dependent node deployment model is presented with the property that the density is inversely proportional to the sink distance. A stochastic model is formulated to examine message advancements…

Probability · Mathematics 2015-03-13 H. Paul Keeler

Jim Propp's rotor router model is a deterministic analogue of a random walk on a graph. Instead of distributing chips randomly, each vertex serves its neighbors in a fixed order. Cooper and Spencer (Comb. Probab. Comput. (2006)) show a…

Combinatorics · Mathematics 2010-06-09 Joshua Cooper , Benjamin Doerr , Tobias Friedrich , Joel Spencer

We introduce a pruning algorithm that provably sparsifies the parameters of a trained model in a way that approximately preserves the model's predictive accuracy. Our algorithm uses a small batch of input points to construct a data-informed…

Machine Learning · Computer Science 2021-03-16 Cenk Baykal , Lucas Liebenwein , Igor Gilitschenski , Dan Feldman , Daniela Rus

We initiate the study of a natural and practically relevant new variant of online caching where the to-be-cached items can have dependencies. We assume that the universe is a tree T and items are tree nodes; we require that if a node v is…

Data Structures and Algorithms · Computer Science 2017-05-16 Marcin Bienkowski , Jan Marcinkowski , Maciej Pacut , Stefan Schmid , Aleksandra Spyra

In this paper, we study an optimal online resource reservation problem in a simple communication network. The network is composed of two compute nodes linked by a local communication link. The system operates in discrete time; at each time…

Optimization and Control · Mathematics 2024-04-04 Ahmed Sid-Ali , Ioannis Lambadaris , Yiqiang Q. Zhao , Gennady Shaikhet , Shima Kheradmand

Online optimization has emerged as powerful tool in large scale optimization. In this paper, we introduce efficient online algorithms based on the alternating directions method (ADM). We introduce a new proof technique for ADM in the batch…

Machine Learning · Computer Science 2012-07-03 Huahua Wang , Arindam Banerjee

We introduce a general framework of stochastic online convex optimization to obtain fast-rate stochastic regret bounds. We prove that algorithms such as online newton steps and a scale-free 10 version of Bernstein online aggregation achieve…

Machine Learning · Computer Science 2023-04-24 Olivier Wintenberger