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On implementing the pushrelabel method for the maximum flow problem
, 1994
"... We study efficient implementations of the pushrelabel method for the maximum flow problem. The resulting codes are faster than the previous codes, and much faster on some problem families. The speedup is due to the combination of heuristics used in our implementation. We also exhibit a family of p ..."
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Cited by 208 (10 self)
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We study efficient implementations of the pushrelabel method for the maximum flow problem. The resulting codes are faster than the previous codes, and much faster on some problem families. The speedup is due to the combination of heuristics used in our implementation. We also exhibit a family of problems for which all known methods seem to have almost quadratic time growth rate.
An Efficient Implementation Of A Scaling MinimumCost Flow Algorithm
 Journal of Algorithms
, 1992
"... . The scaling pushrelabel method is an important theoretical development in the area of minimumcost flow algorithms. We study practical implementations of this method. We are especially interested in heuristics which improve reallife performance of the method. Our implementation works very well o ..."
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Cited by 134 (6 self)
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. The scaling pushrelabel method is an important theoretical development in the area of minimumcost flow algorithms. We study practical implementations of this method. We are especially interested in heuristics which improve reallife performance of the method. Our implementation works very well over a wide range of problem classes. In our experiments, it was always competitive with the established codes, and usually outperformed these codes by a wide margin. Some heuristics we develop may apply to other network algorithms. Our experimental work on the minimumcost flow problem motivated theoretical work on related problems. Supported in part by ONR Young Investigator Award N0001491J1855, NSF Presidential Young Investigator Grant CCR8858097 with matching funds from AT&T and DEC, Stanford University Office of Technology Licensing, and a grant form the Powell Foundation. 1 1. Introduction. Significant theoretical progress has been made recently in the area of minimumcost flow ...
Secure web application via automatic partitioning
 In SOSP ’07
, 2007
"... Swift is a new, principled approach to building web applications that are secure by construction. In modern web applications, some application functionality is usually implemented as clientside code written in JavaScript. Moving code and data to the client can create security vulnerabilities, but c ..."
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Cited by 129 (10 self)
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Swift is a new, principled approach to building web applications that are secure by construction. In modern web applications, some application functionality is usually implemented as clientside code written in JavaScript. Moving code and data to the client can create security vulnerabilities, but currently there are no good methods for deciding when it is secure to do so. Swift automatically partitions application code while providing assurance that the resulting placement is secure and efficient. Application code is written as Javalike code annotated with information flow policies that specify the confidentiality and integrity of web application information. The compiler uses these policies to automatically partition the program into JavaScript code running in the browser, and Java code running on the server. To improve interactive performance, code and data are placed on the client side. However, securitycritical code and data are always placed on the server. Code and data can also be replicated across the client and server, to obtain both security and performance. A maxflow algorithm is used to place code and data in a way that minimizes client–server communication.
An Efficient Cost Scaling Algorithm for the Assignment Problem
 MATH. PROGRAM
, 1995
"... The cost scaling pushrelabel method has been shown to be efficient for solving minimumcost flow problems. In this paper we apply the method to the assignment problem and investigate implementations of the method that take advantage of assignment's special structure. The results show that the ..."
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Cited by 50 (1 self)
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The cost scaling pushrelabel method has been shown to be efficient for solving minimumcost flow problems. In this paper we apply the method to the assignment problem and investigate implementations of the method that take advantage of assignment's special structure. The results show that the method is very promising for practical use.
A Faster Algorithm for Finding the Minimum Cut in a Directed Graph
 JOURNAL OF ALGORITHMS
, 1994
"... We consider the problem of finding the minimum capacity cut in a directed network G with n nodes. This problem has applications to network reliability and survivability and is useful in subroutines for other network optimization problems. One can use a maximum flow problem to find a minimum cut sepa ..."
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Cited by 46 (0 self)
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We consider the problem of finding the minimum capacity cut in a directed network G with n nodes. This problem has applications to network reliability and survivability and is useful in subroutines for other network optimization problems. One can use a maximum flow problem to find a minimum cut separating a designated source node s from a designated sink node t, and by varying the sink node one can find a minimum cut in G as a sequence of at most 2n 2 maximum flow problems. We then show how to reduce the running time of these 2n 2 maximum flow algorithms to the running time for solving a single maximum flow problem. The resulting running time is O(nm log(n 2 /m)) for finding the minimum cut in either a directed or an undirected network. © 1994 Academic Press, Inc. 1.
Experimental Study of Minimum Cut Algorithms
 PROCEEDINGS OF THE EIGHTH ANNUAL ACMSIAM SYMPOSIUM ON DISCRETE ALGORITHMS (SODA)
, 1997
"... Recently, several new algorithms have been developed for the minimum cut problem. These algorithms are very different from the earlier ones and from each other and substantially improve worstcase time bounds for the problem. We conduct experimental evaluation the relative performance of these algor ..."
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Cited by 42 (3 self)
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Recently, several new algorithms have been developed for the minimum cut problem. These algorithms are very different from the earlier ones and from each other and substantially improve worstcase time bounds for the problem. We conduct experimental evaluation the relative performance of these algorithms. In the process, we develop heuristics and data structures that substantially improve practical performance of the algorithms. We also develop problem families for testing minimum cut algorithms. Our work leads to a better understanding of practical performance of the minimum cut algorithms and produces very efficient codes for the problem.
A scalable graphcut algorithm for nd grids
 In Proceedings of CVPR
, 2008
"... Global optimisation via st graph cuts is widely used in computer vision and graphics. To obtain highresolution output, graph cut methods must construct massive ND gridgraphs containing billions of vertices. We show that when these graphs do not fit into physical memory, current maxflow/mincut ..."
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Cited by 41 (0 self)
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Global optimisation via st graph cuts is widely used in computer vision and graphics. To obtain highresolution output, graph cut methods must construct massive ND gridgraphs containing billions of vertices. We show that when these graphs do not fit into physical memory, current maxflow/mincut algorithms—the workhorse of graph cut methods—are totally impractical. Others have resorted to banded or hierarchical approximation methods that get trapped in local minima, which loses the main benefit of global optimisation. We enhance the pushrelabel algorithm for maximum flow [14] with two practical contributions. First, true global minima can now be computed on immense gridlike graphs too large for physical memory. These graphs are ubiquitous in computer vision, medical imaging and graphics. Second, for commodity multicore platforms our algorithm attains nearlinear speedup with respect to number of processors. To achieve these goals, we generalised the standard relabeling operations associated with pushrelabel. 1.
Augment or Push? A computational study of Bipartite Matching and Unit Capacity Flow Algorithms
 ACM J. EXP. ALGORITHMICS
, 1998
"... We conduct a computational study of unit capacity flow and bipartite matching algorithms. Our goal is to determine which variant of the pushrelabel method is most efficient in practice and to compare pushrelabel algorithms with augmenting path algorithms. We have implemented and compared three pus ..."
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Cited by 35 (1 self)
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We conduct a computational study of unit capacity flow and bipartite matching algorithms. Our goal is to determine which variant of the pushrelabel method is most efficient in practice and to compare pushrelabel algorithms with augmenting path algorithms. We have implemented and compared three pushrelabel algorithms, three augmenting path algorithms (one of which is new), and one augmentrelabel algorithm. The depthfirst search augmenting path algorithm was thought to be a good choice for the bipartite matching problem, but our study shows that it is not robust. For the problems we study, our implementations of the fifo and lowestlevel selection pushrelabel algorithms have the most robust asymptotic rate of growth and work best overall. Augmenting path algorithms, although not as robust, on some problem classes are faster by a moderate constant factor. Our study includes several new problem families and input graphs with as many as 5 \Theta 10 5 vertices.
Parametric Maximum Flow Algorithms for Fast Total Variation Minimization
, 2007
"... This report studies the global minimization of discretized total variation (TV) energies with an L¹ or L² fidelity term using parametric maximum flow algorithms. The TVL² model [36], also known as the RudinOsherFatemi (ROF) model is suitable for restoring images contaminated by Gaussian noise, wh ..."
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Cited by 34 (4 self)
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This report studies the global minimization of discretized total variation (TV) energies with an L¹ or L² fidelity term using parametric maximum flow algorithms. The TVL² model [36], also known as the RudinOsherFatemi (ROF) model is suitable for restoring images contaminated by Gaussian noise, while the TVL¹ model [2, 29, 7, 42] is able to remove impulsive noise from greyscale images, and perform multi scale decompositions of them. For largescale applications such as those in medical image (pre)processing, we propose here fast and memoryefficient algorithms, based on a parametric maximum flow algorithm [19] and the minimum st cut representation of TVbased energy functions [26, 17]. Preliminary numerical results on largescale twodimensional CT and threedimensional Brain MRI images that illustrate the effectiveness of our approaches are presented.
Recent developments in maximum flow algorithms (invited lecture
 In SWAT ’98: Proceedings of the 6th Scandinavian Workshop on Algorithm Theory
, 1998
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