The Pseudoflow Algorithm: A New Algorithm for the Maximum-Flow Problem

By D. Hochbaum. 2008

247 citations recorded by the source corpus.

Subfields: Computational Theory and Mathematics, Computer Networks and Communications, Control and Systems Engineering

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Computational Theory and Mathematics

1. James M. Rehg
2. Andres Gomez
3. Sina Aghaei
4. Phebe Vayanos
5. Cristian Sminchisescu
6. Fuxin Li
7. Ahmad Humayun
8. João Carreira

In Computer Networks and Communications

1. James M. Rehg
2. Cristian Sminchisescu
3. Fuxin Li
4. Ahmad Humayun
5. João Carreira

In Control and Systems Engineering

1. James M. Rehg
2. Cristian Sminchisescu
3. Fuxin Li
4. Ahmad Humayun
5. João Carreira

Citations in the corpus

• Learning Optimal Classification Trees: Strong Max-Flow Formulations (2020, background): “Identifying which constraint (8.2) to add can in general be done by solving a minimum cut problem, for which specialized algorithms exist, see Goldberg and Tarjan (1988) and Hochbaum (2008).”
• CPMC: Automatic Object Segmentation Using Constrained Parametric Min-Cuts (2012, methodology): “In this work, we use the highest label pseudoflow solver [60], which has complexity OðmN logðNÞÞ for image graphs with N nodes and m edges.”
• Constrained parametric min-cuts for automatic object segmentation (2010, methodology): “In this work we use thehighest label pseudoflow solver [55], which has complexity ofO(mN log(N)) for image graphs with N nodes andm edges.”
• RIGOR: Reusing Inference in Graph Cuts for Generating Object Regions (2014, methodology): “(a), (b), and (c) give speedup factors for our parametric min-cut when compared to [5], [20], and [17], with increasing number of seeds.”