R.I.P.
👻
Ghosted
Approximation and Kernelization for Chordal Vertex Deletion
May 10, 2016 · Declared Dead · 🏛 ACM-SIAM Symposium on Discrete Algorithms
"No code URL or promise found in abstract"
Evidence collected by the PWNC Scanner
Authors
Bart M. P. Jansen, Marcin Pilipczuk
arXiv ID
1605.03001
Category
cs.DS: Data Structures & Algorithms
Citations
44
Venue
ACM-SIAM Symposium on Discrete Algorithms
Last Checked
3 months ago
Abstract
The Chordal Vertex Deletion (ChVD) problem asks to delete a minimum number of vertices from an input graph to obtain a chordal graph. In this paper we develop a polynomial kernel for ChVD under the parameterization by the solution size, as well as poly(opt) approximation algorithm. The first result answers an open problem of Marx from 2006 [WG 2006, LNCS 4271, 37-48].
Community Contributions
Found the code? Know the venue? Think something is wrong? Let us know!
📜 Similar Papers
In the same crypt — Data Structures & Algorithms
R.I.P.
👻
Ghosted
Relief-Based Feature Selection: Introduction and Review
R.I.P.
👻
Ghosted
Route Planning in Transportation Networks
R.I.P.
👻
Ghosted
Near-linear time approximation algorithms for optimal transport via Sinkhorn iteration
R.I.P.
👻
Ghosted
Hierarchical Clustering: Objective Functions and Algorithms
R.I.P.
👻
Ghosted
Graph Isomorphism in Quasipolynomial Time
Died the same way — 👻 Ghosted
R.I.P.
👻
Ghosted
Language Models are Few-Shot Learners
R.I.P.
👻
Ghosted
PyTorch: An Imperative Style, High-Performance Deep Learning Library
R.I.P.
👻
Ghosted
XGBoost: A Scalable Tree Boosting System
R.I.P.
👻
Ghosted