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Record W7128638588 · doi:10.1109/focs63196.2025.00014

Almost Tight Additive Guarantees for k-Edge-Connectivity

2025· article· W7128638588 on OpenAlex

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

Bibliographic record

Venuenot available
Typearticle
Language
FieldComputer Science
TopicComplexity and Algorithms in Graphs
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsMultigraphVertex connectivityEnhanced Data Rates for GSM EvolutionGraphGraph factorizationConnected componentInduced subgraph isomorphism problemTime complexityConnectivity

Abstract

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We consider the $\boldsymbol{k}$-edge connected spanning subgraph (k-ECSS) problem, where we are given an undirected graph $G=(V, E)$ with nonnegative edge costs $\left\{c_{e}\right\}_{e \in E}$, and the goal is to find a minimum-cost subgraph H of G that is k edge connected, i.e., there exist at least k edge-disjoint paths between every pair of vertices in H. For even k, we present a polynomial time algorithm that computes a ($k-2$)-edge connected subgraph of cost at most that of the optimal k-edge connected subgraph of G; for odd k, we obtain a $(k-3)$ edge connected subgraph of cost at most the optimum. In fact, the cost of our solution does not exceed the optimal value, $\mathbf{L P}_{\boldsymbol{k} \text {-ECSSLP }}^{\boldsymbol{*}}$ of the natural LP-relaxation for $\boldsymbol{k}$-ECSS. Since k-ECSS is $A P X$-hard for all values of $k \geq 2$, our results are nearly optimal. They also significantly improve upon the recent work of Hershkowitz, Klein, and Zenklusen [1], both in terms of solution quality and the simplicity of algorithm and its analysis. Interestingly, our techniques also yield an alternate guarantee, where we obtain a($k-1$)-edge connected subgraph of cost at most $1.5 \cdot \mathrm{LP}_{\boldsymbol{k}-\mathrm{ECSSLP}}^{*}$; with unit edge costs, the cost guarantee improves to $\left(1+\frac{4}{3 k}\right) \cdot$ LP $_{\boldsymbol{k} \text {-ECSSLP }}^{\boldsymbol{*}}$, which improves upon the state-of-the-art approximation guarantee for unit edge costs [2], albeit with a unit loss in edge connectivity. Our k-ECSS-result also yields results for the k-edge connected spanning multigraph (k-ECSM) problem, where multiple copies of an edge can be selected. For $\boldsymbol{k}$-ECSM, we obtain a $\left(1+\frac{2}{k}\right)$-approximation algorithm for even k, and $\mathbf{a}\left(1+\frac{3}{k}\right)$ approximation algorithm for odd $\boldsymbol{k}$. Finally, our techniques extend to the degree-bounded versions of k-ECSS and k-ECSM, wherein we also impose degree lower- and upper- bounds on the nodes. Our results for k-ECSS and k-ECSM extend to yield the same cost and connectivity guarantees for these degree-bounded versions with an additive violation of (roughly) 2 for the degree bounds. These are the first results for degree-bounded $\{k$-ECSS, k-ECSM $\}$ of the form where the cost of the solution obtained is at most the optimum, and the connectivity constraints are violated by an additive constant. Work done while N. Kumar was a postdoc in the $C \& O$ department at the University of Waterloo. Supported in part by C. Swamy’s NSERC Discovery grant.

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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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.790
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.002
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0020.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.021
GPT teacher head0.283
Teacher spread0.262 · 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

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Citations0
Published2025
Admission routes1
Has abstractyes

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