Robust Factorizations and Colorings of Tensor Graphs
Joshua Brakensiek, Sami Davies

TL;DR
This paper investigates the 3-coloring problem for graphs derived from tensor products, introducing approximation algorithms for certain cases and proving NP-hardness in general, thus advancing understanding of coloring tensor graphs.
Contribution
The paper introduces methods for approximating and coloring tensor product graphs, extending tensor factorization techniques and establishing NP-hardness results.
Findings
Polynomial-time 3-coloring for tensor graphs with mild expanders.
Approximate tensor factorization close to original graphs.
NP-hardness of 3-coloring in general tensor product graphs.
Abstract
Since the seminal result of Karger, Motwani, and Sudan, algorithms for approximate 3-coloring have primarily centered around SDP-based rounding. However, it is likely that important combinatorial or algebraic insights are needed in order to break the threshold. One way to develop new understanding in graph coloring is to study special subclasses of graphs. For instance, Blum studied the 3-coloring of random graphs, and Arora and Ge studied the 3-coloring of graphs with low threshold-rank. In this work, we study graphs which arise from a tensor product, which appear to be novel instances of the 3-coloring problem. We consider graphs of the form with and , where is any edge set such that no vertex has more than an fraction of its edges in . We show that one can…
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
TopicsLimits and Structures in Graph Theory
