Palette Sparsification via FKNP
Vikrant Ashvinkumar, Charles Kenney

TL;DR
This paper establishes a connection between spread distributions and palette sparsification, providing a new probabilistic framework for coloring graphs with bounded degree.
Contribution
It introduces a novel use of spread distributions to derive palette sparsification results for graphs with bounded maximum degree.
Findings
Existence of a $C/D$-spread distribution for $(D+1)$-colorings
Application of Frankston, Kahn, Narayanan, and Park's threshold-spread connection
Derivation of a palette sparsification theorem for bounded degree graphs
Abstract
A random set is -spread if, for all sets , There is a constant large enough that for every graph with maximum degree , there is a -spread distribution on -colorings of . Making use of a connection between thresholds and spread distributions due to Frankston, Kahn, Narayanan, and Park, a palette sparsification theorem of Assadi, Chen, and Khanna follows.
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsAdvanced Numerical Analysis Techniques · Handwritten Text Recognition Techniques · Machine Learning and Algorithms
