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61
Fast approximate energy minimization with label costs
, 2010
"... The αexpansion algorithm [7] has had a significant impact in computer vision due to its generality, effectiveness, and speed. Thus far it can only minimize energies that involve unary, pairwise, and specialized higherorder terms. Our main contribution is to extend αexpansion so that it can simult ..."
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Cited by 45 (6 self)
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The αexpansion algorithm [7] has had a significant impact in computer vision due to its generality, effectiveness, and speed. Thus far it can only minimize energies that involve unary, pairwise, and specialized higherorder terms. Our main contribution is to extend αexpansion so that it can simultaneously optimize “label costs ” as well. An energy with label costs can penalize a solution based on the set of labels that appear in it. The simplest special case is to penalize the number of labels in the solution. Our energy is quite general, and we prove optimality bounds for our algorithm. A natural application of label costs is multimodel fitting, and we demonstrate several such applications in vision: homography detection, motion segmentation, and unsupervised image segmentation. Our C++/MATLAB implementation is publicly available.
Facility Location with Nonuniform Hard Capacities
 Proceedings of the 42nd IEEE Symposium on the Foundations of Computer Science
, 2001
"... In this paper we give the first constant factor approximation algorithm for the Facility Location Problem with nonuniform, hard capacities. Facility location problems have received a great deal of attention in recent years. Approximation algorithms have been developed for many variants. Most of thes ..."
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Cited by 41 (0 self)
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In this paper we give the first constant factor approximation algorithm for the Facility Location Problem with nonuniform, hard capacities. Facility location problems have received a great deal of attention in recent years. Approximation algorithms have been developed for many variants. Most of these algorithms are based on linear programming, but the LP techniques developed thus far have been unsuccessful in dealing with hard capacities.
A Hybrid Heuristic for the pMedian Problem
, 2003
"... Given n customers and a set F of m potential facilities, the pmedian problem consists in finding a subset of F with p facilities such that the cost of serving all customers is minimized. ..."
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Cited by 32 (10 self)
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Given n customers and a set F of m potential facilities, the pmedian problem consists in finding a subset of F with p facilities such that the cost of serving all customers is minimized.
Universal Facility Location
 in Proc. of ESA ’03
, 2003
"... In the Universal Facility Location problem we are given a set of demand points and a set of facilities. ..."
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Cited by 26 (0 self)
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In the Universal Facility Location problem we are given a set of demand points and a set of facilities.
A MultiExchange Local Search Algorithm for the Capacitated Facility Location Problem
 Mathematics of Operations Research
, 2004
"... We present a multiexchange local search algorithm for approximating the capacitated facility location problem (CFLP), where a new local improvement operation is introduced that possibly exchanges multiple facilities simultaneously. We give a tight analysis for our algorithm and show that the per ..."
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Cited by 22 (0 self)
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We present a multiexchange local search algorithm for approximating the capacitated facility location problem (CFLP), where a new local improvement operation is introduced that possibly exchanges multiple facilities simultaneously. We give a tight analysis for our algorithm and show that the performance guarantee of the algorithm is between 3+ 2 # 2 # and 3+ 2 # 2+ # for any given constant # > 0. Previously known best approximation ratio for the CFLP is 7.88, due to Mahdian and Pal (2003), based on the operations proposed by Pal, Tardos and Wexler (2001).
Separability as an approach to physical database design
, 1981
"... Abstract A theoretical approach to the optimal design of a large multifile'physical database is presented. The design algorithm is based on the theory that, given a set of join methods that satisfy a certain property called separability, the problem of optimal assignment of access structures to the ..."
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Cited by 18 (7 self)
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Abstract A theoretical approach to the optimal design of a large multifile'physical database is presented. The design algorithm is based on the theory that, given a set of join methods that satisfy a certain property called separability, the problem of optimal assignment of access structures to the whole database can be reduced to the subproblem of optimizing individual relations independently of one another. Coupling factors are defined to represent all the interactions among the relations. This approach not only reduces the complexity of the problem significantly, but also provides a better understanding of underlying mechanisms. Index TermsBlock accesses, index selection, join methods, physical database design, query optimization, selectivity. I.
Optimizing the placement of integration points in multihop wireless networks
 IN PROCEEDINGS OF ICNP
, 2004
"... Efficient integration of a multihop wireless network with the Internet is an important research problem, and benefits several applications, such as wireless neighborhood networks and sensor networks. In a wireless neighborhood network, a few Internet Transit Access Points (ITAPs), serving as gatewa ..."
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Cited by 17 (2 self)
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Efficient integration of a multihop wireless network with the Internet is an important research problem, and benefits several applications, such as wireless neighborhood networks and sensor networks. In a wireless neighborhood network, a few Internet Transit Access Points (ITAPs), serving as gateways to the Internet, are deployed across the neighborhood; houses are equipped with lowcost antennas, and form a multihop wireless network among themselves to cooperatively route traffic to the Internet through the ITAPs. In a sensor network, sensors collect measurement data and send it through a multihop wireless network to the servers on the Internet via ITAPs. For both applications, placement of integration points between the wireless and wired network is a critical determinant of system performance and resource usage. However there has been little work on this subject. In this paper, we explore the placement problem under three wireless link models. For each link model, we develop algorithms to make informed placement decisions based on neighborhood layouts, user demands, and wireless link characteristics. We also extend our algorithms to provide fault tolerance and handle significant workload variation. We evaluate our placement algorithms using both analysis and simulation, and show that our algorithms yield close to optimal solutions over a wide range of scenarios we have considered.
A Hybrid Multistart Heuristic for the Uncapacitated Facility Location Problem
, 2003
"... We present a multistart heuristic for the uncapacitated facility location problem, based on a very successful method we originally developed for the pmedian problem. ..."
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Cited by 16 (3 self)
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We present a multistart heuristic for the uncapacitated facility location problem, based on a very successful method we originally developed for the pmedian problem.
On the Placement of Internet Taps in Wireless Neighborhood Networks
, 2003
"... Recently there has emerged a novel application of wireless technology that enables home users to connect to the Internet by creating a multihop wireless network over a neighborhood region. In such a network, a small number of Internet TAPs (ITAPs) are deployed across the neighborhood, serving as g ..."
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Cited by 15 (1 self)
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Recently there has emerged a novel application of wireless technology that enables home users to connect to the Internet by creating a multihop wireless network over a neighborhood region. In such a network, a small number of Internet TAPs (ITAPs) are deployed across the neighborhood, serving as gateways to the Internet; houses are equipped with lowcost antennas, and form a multihop wireless network among themselves to cooperatively route traffic to the Internet using the ITAPs. A similar application also exists in sensor networks, where sensors collect measurement data and send it through a multihop wireless network to the servers on the Internet via ITAPs. For both applications, placement of ITAPs is a critical determinant of system performance and resource usage. However there has been little work on this subject. In this paper, we explore the ITAP placement problem under three wireless link models. For each link model, we develop placement algorithms to make informed placement decisions based on neighborhood layouts, user demands, and wireless link characteristics. We also extend our algorithms to provide fault tolerance and to handle significant workload variation. We evaluate our placement algorithms through both analysis and simulation. Our results show that our algorithms yield close to optimal solutions over a wide range of scenarios we have considered.
Gamps: Compressing multi sensor data by grouping and amplitude scaling
 In: ACM SIGMOD. (2009
"... We consider the problem of collectively approximating a set of sensor signals using the least amount of space so that any individual signal can be efficiently reconstructed within a given maximum (L∞) error ε. The problem arises naturally in applications that need to collect large amounts of data fr ..."
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Cited by 14 (0 self)
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We consider the problem of collectively approximating a set of sensor signals using the least amount of space so that any individual signal can be efficiently reconstructed within a given maximum (L∞) error ε. The problem arises naturally in applications that need to collect large amounts of data from multiple concurrent sources, such as sensors, servers and network routers, and archive them over a long period of time for offline data mining. We present GAMPS, a general framework that addresses this problem by combining several novel techniques. First, it dynamically groups multiple signals together so that signals within each group are correlated and can be maximally compressed jointly. Second, it appropriately scales the amplitudes of different signals within a group and compresses them within the maximum allowed reconstruction error bound. Our schemes are polynomial time O(α, β) approximation schemes, meaning that the maximum (L∞) error is at most αε and it uses at most β times the optimal memory. Finally, GAMPS maintains an index so that various queries can be issued directly on compressed data. Our experiments on several realworld sensor datasets show that GAMPS significantly reduces space without compromising the quality of search and query. Categories and Subject Descriptors