A Randomized Algorithm for Long Directed Cycle
October 29, 2015 Β· Declared Dead Β· π Information Processing Letters
"No code URL or promise found in abstract"
Evidence collected by the PWNC Scanner
Authors
Meirav Zehavi
arXiv ID
1510.08892
Category
cs.DS: Data Structures & Algorithms
Citations
18
Venue
Information Processing Letters
Last Checked
3 months ago
Abstract
Given a directed graph $G$ and a parameter $k$, the {\sc Long Directed Cycle (LDC)} problem asks whether $G$ contains a simple cycle on at least $k$ vertices, while the {\sc $k$-Path} problems asks whether $G$ contains a simple path on exactly $k$ vertices. Given a deterministic (randomized) algorithm for {\sc $k$-Path} as a black box, which runs in time $t(G,k)$, we prove that {\sc LDC} can be solved in deterministic time $O^*(\max\{t(G,2k),4^{k+o(k)}\})$ (randomized time $O^*(\max\{t(G,2k),4^k\})$). In particular, we get that {\sc LDC} can be solved in randomized time $O^*(4^k)$.
Community Contributions
Found the code? Know the venue? Think something is wrong? Let us know!
π Similar Papers
In the same crypt β Data Structures & Algorithms
π
π
The Cartographer
R.I.P.
π»
Ghosted
Route Planning in Transportation Networks
R.I.P.
π»
Ghosted
Near-linear time approximation algorithms for optimal transport via Sinkhorn iteration
R.I.P.
π»
Ghosted
Hierarchical Clustering: Objective Functions and Algorithms
R.I.P.
π»
Ghosted
Graph Isomorphism in Quasipolynomial Time
π
π
The Cartographer
Simulation optimization: A review of algorithms and applications
Died the same way β π» Ghosted
R.I.P.
π»
Ghosted
Federated Learning: Strategies for Improving Communication Efficiency
R.I.P.
π»
Ghosted
In-Datacenter Performance Analysis of a Tensor Processing Unit
R.I.P.
π»
Ghosted
Deep Convolutional Neural Networks for Computer-Aided Detection: CNN Architectures, Dataset Characteristics and Transfer Learning
R.I.P.
π»
Ghosted