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Push-Relabel is one of the most celebrated network flow algorithms.
“Maximal flow through a network”
Lester Ford and Delbert Fulkerson · 1956
Earlier work this paper cites.
“A new approach to the maximum-flow problem”
Andrew Goldberg and Robert Tarjan · 1988
Earlier work this paper cites.
“Network flows and matching: first DIMACS implementation challenge”
David Johnson and Catherine McGeoch · 1993
Earlier work this paper cites.
“On implementing push-relabel method for the maximum flow problem”
Boris Cherkassky and Andrew Goldberg · 1995
Earlier work this paper cites.
“Computational investigations of maximum flow algorithms”
Ravindra Ahuja, Murali Kodialam, Ajay Mishra and James Orlin · 1997
Earlier work this paper cites.
“Interactive graph cuts for optimal boundary & region segmentation of objects in ND images”
Yuri Boykov and M.P. Jolly · 2001
Earlier work this paper cites.
“An experimental comparison of min-cut/max-flow algorithms for energy minimization in vision”
Yuri Boykov and Vladimir Kolmogorov · 2004
Earlier work this paper cites.
“Graph cuts and efficient ND image segmentation”
Yuri Boykov and Gareth Funka-Lea · 2006
Earlier work this paper cites.
“Applications of parametric maxflow in computer vision”
Vladimir Kolmogorov, Yuri Boykov and Carsten Rother · 2007
Earlier work this paper cites.
“The partial augment–relabel algorithm for the maximum flow problem”
Andrew Goldberg · 2008
Cited alongside, same era.
“The pseudoflow algorithm: A new algorithm for the maximum-flow problem”
Dorit Hochbaum · 2008
Cited alongside, same era.
“A computational study of the pseudoflow and push-relabel algorithms for the maximum flow problem”
Bala Chandran and Dorit Hochbaum · 2009
Cited alongside, same era.
“Faster and more dynamic maximum flow by incremental breadth-first search”
Andrew Goldberg, Sagi Hed, Haim Kaplan, Pushmeet Kohli, Robert Tarjan and Renato Werneck · 2015
Cited alongside, same era.
“The case for learned index structures”
Tim Kraska, Alex Beutel, Ed Chi, Jeffrey Dean and Neoklis Polyzotis · 2018
Cited alongside, same era.
“Network flow algorithms”
David Williamson · 2019
Cited alongside, same era.
“Faster fundamental graph algorithms via learned predictions”
Justin Chen, Sandeep Silwal, Ali Vakilian and Fred Zhang · 2022
Later among the works it cites.
“Maximum flow and minimum-cost flow in almost-linear time”
Li Chen, Rasmus Kyng, Yang Liu, Richard Peng, Maximilian Gutenberg and Sushant Sachdeva · 2022
Later among the works it cites.
“Learning augmented binary search trees”
Honghao Lin, Tian Luo and David Woodruff · 2022
Later among the works it cites.
“Algorithms with predictions”
Michael Mitzenmacher and Sergei Vassilvitskii · 2022
Later among the works it cites.
“Learning-augmented maximum flow”
Adam Polak and Maksym Zub · 2022
Later among the works it cites.
“Robust load balancing with machine learned advice”
Sara Ahmadian, Hossein Esfandiari, Vahab Mirrokni and Binghui Peng · 2023
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“Predictive Flows for Faster Ford-Fulkerson”
Sami Davies, Benjamin Moseley, Sergei Vassilvitskii and Yuyan Wang · 2023
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“Minimalistic predictions to schedule jobs with online precedence constraints”
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