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Record W2753502872

Reconfiguring Graph Colorings

2017· dissertation· en· W2753502872 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueUWSpace (University of Waterloo) · 2017
Typedissertation
Languageen
FieldDecision Sciences
TopicScheduling and Timetabling Solutions
Canadian institutionsBlackberry (Canada)
Fundersnot available
KeywordsComputer scienceCombinatoricsMathematics
DOInot available

Abstract

fetched live from OpenAlex

Graph coloring has been studied for a long time and continues to receive
\ninterest within the research community \\cite{kubale2004graph}. It has applications
\nin scheduling \\cite{daniel2004graph}, timetables, and compiler register
\nallocation \\cite{lewis2015guide}. The most popular variant of graph coloring,
\nk-coloring, can be thought of as an assignment of $k$ colors to the vertices of a
\ngraph such that adjacent vertices are assigned different colors.
\n
\nReconfiguration problems, typically defined on the solution space of search problems,
\nbroadly ask whether one solution can be transformed to another solution using
\nstep-by-step transformations, when constrained to one or more specific transformation
\nsteps \\cite{van2013complexity}. One well-studied reconfiguration problem is the
\nproblem of deciding whether one k-coloring can be transformed to another k-coloring
\nby changing the color of one vertex at a time, while always maintaining a k-coloring
\nat each step.
\n
\nWe consider two variants of graph coloring: acyclic coloring and equitable
\ncoloring, and their corresponding reconfiguration problems. A k-acylic coloring is
\na k-coloring where there are more than two colors used by the vertices of each
\ncycle, and a k-equitable coloring is a k-coloring such that each color class, which is
\ndefined as the set of all vertices with a particular color, is nearly the same
\nsize as all others.
\n
\nWe show that reconfiguration of acyclic colorings is PSPACE-hard, and that for
\nnon-bipartite graphs with chromatic number 3 there exist two k-acylic colorings
\n$f_s$ and $f_e$ such that there is no sequence of transformations that can
\ntransform $f_s$ to $f_e$. We also consider the problem of whether two
\nk-acylic colorings can be transformed to each other in at most $\\ell$ steps, and
\nshow that it is in XP, which is the class of algorithms that run in time
\n$O(n^{f(k)})$ for some computable function $f$ and parameter $k$, where in this
\ncase the parameter is defined to be the length of the reconfiguration sequence
\nplus the length of the longest induced cycle.
\n
\nWe also show that the reconfiguration of equitable colorings is PSPACE-hard
\nand W[1]-hard with respect to the number of vertices with the same color. We
\ngive polynomial-time algorithms for Reconfiguration of Equitable Colorings when
\nthe number of colors used is two and also for paths when the number of colors
\nused is three.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.805
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0020.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.001

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.066
GPT teacher head0.304
Teacher spread0.237 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it