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We propose a fast approximate algorithm for large graph matching. A new projected fixed-point method is defined and a new doubly stochastic projection is adopted to derive the algorithm. Previous graph matching algorithms suffer from high…

Computer Vision and Pattern Recognition · Computer Science 2012-08-13 Yao Lu , Kaizhu Huang , Cheng-Lin Liu

Within the context of stochastic probing with commitment, we consider the online stochastic matching problem; that is, the one sided online bipartite matching problem where edges adjacent to an online node must be probed to determine if…

Data Structures and Algorithms · Computer Science 2021-01-07 Allan Borodin , Calum MacRury , Akash Rakheja

The maximum a posteriori (MAP) inference for determinantal point processes (DPPs) is crucial for selecting diverse items in many machine learning applications. Although DPP MAP inference is NP-hard, the greedy algorithm often finds…

Data Structures and Algorithms · Computer Science 2022-06-14 Shinichi Hemmi , Taihei Oki , Shinsaku Sakaue , Kaito Fujii , Satoru Iwata

In this paper, we present a framework used to construct and analyze algorithms for online optimization problems with deadlines or with delay over a metric space. Using this framework, we present algorithms for several different problems. We…

Data Structures and Algorithms · Computer Science 2019-04-16 Yossi Azar , Noam Touitou

Online bipartite matching with edge arrivals remained a major open question for a long time until a recent negative result by [Gamlath et al. FOCS 2019], who showed that no online policy is better than the straightforward greedy algorithm,…

Data Structures and Algorithms · Computer Science 2020-07-17 Nick Gravin , Zhihao Gavin Tang , Kangning Wang

As foundation models grow in size, fine-tuning them becomes increasingly expensive. While GPU spot instances offer a low-cost alternative to on-demand resources, their volatile prices and availability make deadline-aware scheduling…

Distributed, Parallel, and Cluster Computing · Computer Science 2025-12-25 Linggao Kong , Yuedong Xu , Lei Jiao , Chuan Xu

This paper develops learning-augmented algorithms for energy trading in volatile electricity markets. The basic problem is to sell (or buy) $k$ units of energy for the highest revenue (lowest cost) over uncertain time-varying prices, which…

Machine Learning · Computer Science 2024-02-29 Russell Lee , Bo Sun , Mohammad Hajiesmaili , John C. S. Lui

This paper considers the classic Online Steiner Forest problem where one is given a (weighted) graph $G$ and an arbitrary set of $k$ terminal pairs $\{\{s_1,t_1\},\ldots ,\{s_k,t_k\}\}$ that are required to be connected. The goal is to…

Data Structures and Algorithms · Computer Science 2021-11-22 Étienne Bamas , Marina Drygala , Andreas Maggiori

In this paper we consider the Stochastic Matching problem, which is motivated by applications in kidney exchange and online dating. We are given an undirected graph in which every edge is assigned a probability of existence and a positive…

Data Structures and Algorithms · Computer Science 2015-05-07 Marek Adamczyk , Fabrizio Grandoni , Joydeep Mukherjee

We consider online scheduling weighted packets with time constraints over a fading channel. Packets arrive at the transmitter in an online manner. Each packet has a value and a deadline by which it should be sent. The fade state of the…

Information Theory · Computer Science 2009-09-30 Fei Li , Zhi Zhang

An online truthful budgeted matching problem is considered for a bipartite graph, where the right vertices are available ahead of time, and individual left vertices arrive sequentially. On arrival of a left vertex, its edge utilities (or…

Data Structures and Algorithms · Computer Science 2016-06-03 Rahul Vaze , Marceau Coupechoux

MapReduce has become the de facto standard model for designing distributed algorithms to process big data on a cluster. There has been considerable research on designing efficient MapReduce algorithms for clustering, graph optimization, and…

Data Structures and Algorithms · Computer Science 2018-06-19 Nicholas J. A. Harvey , Christopher Liaw , Paul Liu

Inspired by sequential budgeted allocation problems, we study the online matching problem with budget refills. In this context, we consider an online bipartite graph $G=(U,V,E)$, where the nodes in $V$ are discovered sequentially and nodes…

Data Structures and Algorithms · Computer Science 2025-07-08 Maria Cherifa , Clément Calauzènes , Vianney Perchet

We reinterpret some online greedy algorithms for a class of nonlinear "load-balancing" problems as solving a mathematical program online. For example, we consider the problem of assigning jobs to (unrelated) machines to minimize the sum of…

Data Structures and Algorithms · Computer Science 2011-09-28 Anupam Gupta , Ravishankar Krishnaswamy , Kirk Pruhs

For compressed sensing over arbitrarily connected networks, we consider the problem of estimating underlying sparse signals in a distributed manner. We introduce a new signal model that helps to describe inter-signal correlation among…

Information Theory · Computer Science 2013-10-29 Dennis Sundman , Saikat Chatterjee , Mikael Skoglund

In this paper we prove the efficacy of a simple greedy algorithm for a finite horizon online resource allocation/matching problem, when the corresponding static planning linear program (SPP) exhibits a non-degeneracy condition called the…

Data Structures and Algorithms · Computer Science 2022-07-26 Varun Gupta

We consider a parallel system of $m$ identical machines prone to unpredictable crashes and restarts, trying to cope with the continuous arrival of tasks to be executed. Tasks have different computational requirements (i.e., processing time…

Distributed, Parallel, and Cluster Computing · Computer Science 2016-03-21 Elli Zavou , Antonio Fernández Anta

Motivated by an application in kidney exchange, we study the following query-commit problem: we are given the set of vertices of a non-bipartite graph G. The set of edges in this graph are not known ahead of time. We can query any pair of…

Data Structures and Algorithms · Computer Science 2013-08-26 Gagan Goel , Pushkar Tripathi

It is known that greedy methods perform well for maximizing monotone submodular functions. At the same time, such methods perform poorly in the face of non-monotonicity. In this paper, we show - arguably, surprisingly - that invoking the…

Machine Learning · Computer Science 2017-04-07 Moran Feldman , Christopher Harshaw , Amin Karbasi

The problem of online matching with stochastic rewards is a generalization of the online bipartite matching problem where each edge has a probability of success. When a match is made it succeeds with the probability of the corresponding…

Data Structures and Algorithms · Computer Science 2022-05-12 Vineet Goyal , Rajan Udwani