A Simple Distributed Algorithm for Sparse Fractional Covering and Packing Problems
September 24, 2024 Β· Declared Dead Β· π International Symposium on Algorithms and Computation
"No code URL or promise found in abstract"
Evidence collected by the PWNC Scanner
Authors
Qian Li, Minghui Ouyang, Yuyi Wang
arXiv ID
2409.16168
Category
cs.DS: Data Structures & Algorithms
Cross-listed
cs.DC
Citations
0
Venue
International Symposium on Algorithms and Computation
Last Checked
5 months ago
Abstract
This paper presents a distributed algorithm in the CONGEST model that achieves a $(1+Ξ΅)$-approximation for row-sparse fractional covering problems (RS-FCP) and the dual column-sparse fraction packing problems (CS-FPP). Compared with the best-known $(1+Ξ΅)$-approximation CONGEST algorithm for RS-FCP/CS-FPP developed by Kuhn, Moscibroda, and Wattenhofer (SODA'06), our algorithm is not only much simpler but also significantly improves the dependency on $Ξ΅$.
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