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Jacob W. Cooper

dblp:166/1219 · DBLP profile ↗
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2ranked-venue papers
0as first author
1since 2021 · last 2022
0000-0003-3049-6249ORCID · corroborated

Domains — the database's venue-derived domains; a paper can count in several

Theory of computation · 2 · 1 since 2021

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Theoretical computer science
2 papers
Mathematical optimization · 29% Computational complexity · 29% Combinatorics and discrete mathematics · 29%

Topics — the 4 heaviest of 4, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Computational complexity › parameterized complexity
fixed-parameter tractability
1.022022
Matrices of Optimal Tree-Depth and a Row-Invariant Parameterized Algorithm for Integer Programming · SIAM J. Comput. 2022
Matrices of Optimal Tree-Depth and Row-Invariant Parameterized Algorithm for Integer Programming · ICALP 2020
Mathematical optimization
integer programming
1.022022
Matrices of Optimal Tree-Depth and a Row-Invariant Parameterized Algorithm for Integer Programming · SIAM J. Comput. 2022
Matrices of Optimal Tree-Depth and Row-Invariant Parameterized Algorithm for Integer Programming · ICALP 2020
Combinatorics and discrete mathematics
matroid theory
1.022022
Matrices of Optimal Tree-Depth and a Row-Invariant Parameterized Algorithm for Integer Programming · SIAM J. Comput. 2022
Matrices of Optimal Tree-Depth and Row-Invariant Parameterized Algorithm for Integer Programming · ICALP 2020
Graph algorithms and graph theory › graph theory › graph parameters › graph width parameters
treedepth
0.412020
Matrices of Optimal Tree-Depth and Row-Invariant Parameterized Algorithm for Integer Programming · ICALP 2020

Methods — techniques the papers use, named apart from their topics

matroid representation · 0.6fixed-parameter algorithms · 0.6parameterized complexity · 0.4matroid theory · 0.4
YearPublicationVenuePosition
2022 Matrices of Optimal Tree-Depth and a Row-Invariant Parameterized Algorithm for Integer Programming
abstract
A long line of research on fixed parameter tractability of integer programming culminated with showing that integer programs with $n$ variables and a constraint matrix with dual tree-depth $d$ and largest entry $\Delta$ are solvable in time $g(d,\Delta){poly}(n)$ for some function $g$. However, the dual tree-depth of a constraint matrix is not preserved by row operations, i.e., a given integer program can be equivalent to another with a smaller dual tree-depth, and thus does not reflect its geometric structure. We prove that the minimum dual tree-depth of a row-equivalent matrix is equal to the branch-depth of the matroid defined by the columns of the matrix. We design a fixed parameter algorithm for computing branch-depth of matroids represented over a finite field and a fixed parameter algorithm for computing a row-equivalent matrix with minimum dual tree-depth. Finally, we use these results to obtain an algorithm for integer programming running in time $g(d^*,\Delta){poly}(n)$ where $d^*$ is the branch-depth of the constraint matrix; the branch-depth cannot be replaced by the more permissive notion of branch-width.
Timothy F. N. Chan, Jacob W. Cooper, Martin Koutecký, Daniel Král, Kristýna Pekárková
SIAM J. Comput.2
2020 Matrices of Optimal Tree-Depth and Row-Invariant Parameterized Algorithm for Integer Programming
abstract
A long line of research on fixed parameter tractability of integer programming culminated with showing that integer programs with n variables and a constraint matrix with tree-depth d and largest entry Δ are solvable in time g(d,Δ) poly(n) for some function g, i.e., fixed parameter tractable when parameterized by tree-depth d and Δ. However, the tree-depth of a constraint matrix depends on the positions of its non-zero entries and thus does not reflect its geometric structure. In particular, tree-depth of a constraint matrix is not preserved by row operations, i.e., a given integer program can be equivalent to another with a smaller dual tree-depth. We prove that the branch-depth of the matroid defined by the columns of the constraint matrix is equal to the minimum tree-depth of a row-equivalent matrix. We also design a fixed parameter algorithm parameterized by an integer d and the entry complexity of an input matrix that either outputs a matrix with the smallest dual tree-depth that is row-equivalent to the input matrix or outputs that there is no matrix with dual tree-depth at most d that is row-equivalent to the input matrix. Finally, we use these results to obtain a fixed parameter algorithm for integer programming parameterized by the branch-depth of the input constraint matrix and the entry complexity. The parameterization by branch-depth cannot be replaced by the more permissive notion of branch-width.
Timothy F. N. Chan, Jacob W. Cooper, Martin Koutecký, Daniel Král, Kristýna Pekárková
ICALP2