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The Nature of Statistical Learning Theory
, 1999
"... Statistical learning theory was introduced in the late 1960’s. Until the 1990’s it was a purely theoretical analysis of the problem of function estimation from a given collection of data. In the middle of the 1990’s new types of learning algorithms (called support vector machines) based on the deve ..."
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Cited by 12976 (32 self)
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Statistical learning theory was introduced in the late 1960’s. Until the 1990’s it was a purely theoretical analysis of the problem of function estimation from a given collection of data. In the middle of the 1990’s new types of learning algorithms (called support vector machines) based
The Pseudoflow algorithm: A new algorithm for the maximum flow problem
 Operations Research
, 2008
"... We introduce the pseudoflow algorithm for the maximumflow problem that employs only pseudoflows and does not generate flows explicitly. The algorithm solves directly a problem equivalent to the minimumcut problem—the maximum blockingcut problem. Once the maximum blockingcut solution is available ..."
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Cited by 38 (12 self)
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is available, the additional complexity required to find the respective maximumflow is O�mlog n�. A variant of the algorithm is a new parametric maximumflow algorithm generating all breakpoints in the same complexity required to solve the constant capacities maximumflow problem. The pseudoflow algorithm has
The Pseudoflow algorithm: A new algorithm for the maximum flow problem
"... We introduce the pseudoflow algorithm for the maximum flow problem that employs only pseudoflows and does not generate flows explicitly. The algorithm solves directly a problem equivalent to the minimum cut problem – the maximum blocking cut problem. Once the maximum blocking cut solution is availab ..."
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is available, the additional complexity required to find the respective maximum flow is O(m log n). A variant of the algorithm is a new parametric maximum flow algorithm generating all breakpoints in the same complexity required to solve the constant capacities maximum flow problem. The pseudoflow algorithm
The Pseudoflow Algorithm and the PseudoflowBased Simplex for the Maximum Flow Problem
 In 6th IPCO
, 1998
"... . We introduce an algorithm that solves the maximum flow problem without generating flows explicitly. The algorithm solves directly a problem we call the maximum sexcess problem. That problem is equivalent to the minimum cut problem, and is a direct extension of the maximum closure problem. The con ..."
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Cited by 12 (0 self)
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. The concepts used also lead to a new parametric analysis algorithm generating all breakpoints in the amount of time of a single run. The insights derived from the analysis of the new algorithm lead to a new simplex algorithm for the maximum flow problem  a pseudoflowbased simplex. We show that this simplex
A new approach to the maximum flow problem
 JOURNAL OF THE ACM
, 1988
"... All previously known efficient maximumflow algorithms work by finding augmenting paths, either one path at a time (as in the original Ford and Fulkerson algorithm) or all shortestlength augmenting paths at once (using the layered network approach of Dinic). An alternative method based on the pre ..."
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Cited by 672 (34 self)
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All previously known efficient maximumflow algorithms work by finding augmenting paths, either one path at a time (as in the original Ford and Fulkerson algorithm) or all shortestlength augmenting paths at once (using the layered network approach of Dinic). An alternative method based
Simplifications and speedups of the Pseudoflow algorithm
 NETWORKS
, 2013
"... The pseudoflow algorithm for solving the maximum flow and minimum cut problems was devised in Hochbaum (2008). The complexity of the algorithm was shown in (2008) to be O(nm log n). Chandran and Hochbaum, (2009) demonstrated that the pseudoflow algorithm is very efficient in practice, and that the h ..."
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Cited by 3 (3 self)
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FirstSearch implementation that is likely to be fast in practice as well. In addition, we give a new simpler description of the pseudoflow algorithm by relating it to the simplex algorithm as applied to the maximum preflow problem defined here. The interpretation of the generic pseudoflow algorithm as a simplex
Theoretical improvements in algorithmic efficiency for network flow problems

, 1972
"... This paper presents new algorithms for the maximum flow problem, the Hitchcock transportation problem, and the general minimumcost flow problem. Upper bounds on ... the numbers of steps in these algorithms are derived, and are shown to compale favorably with upper bounds on the numbers of steps req ..."
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Cited by 565 (0 self)
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This paper presents new algorithms for the maximum flow problem, the Hitchcock transportation problem, and the general minimumcost flow problem. Upper bounds on ... the numbers of steps in these algorithms are derived, and are shown to compale favorably with upper bounds on the numbers of steps
A MaximumFlow Formulation of the Ncamera Stereo Correspondence Problem
, 1998
"... This paper describes a new algorithm for solving the Ncamera stereo correspondence problem by transforming it into a maximumflow problem. Once solved, the minimumcut associated to the maximumflow yields a disparity surface for the whole image at once. This global approach to stereo analysis provi ..."
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Cited by 263 (4 self)
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This paper describes a new algorithm for solving the Ncamera stereo correspondence problem by transforming it into a maximumflow problem. Once solved, the minimumcut associated to the maximumflow yields a disparity surface for the whole image at once. This global approach to stereo analysis
Planning Algorithms
, 2004
"... This book presents a unified treatment of many different kinds of planning algorithms. The subject lies at the crossroads between robotics, control theory, artificial intelligence, algorithms, and computer graphics. The particular subjects covered include motion planning, discrete planning, planning ..."
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Cited by 1108 (51 self)
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This book presents a unified treatment of many different kinds of planning algorithms. The subject lies at the crossroads between robotics, control theory, artificial intelligence, algorithms, and computer graphics. The particular subjects covered include motion planning, discrete planning
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