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PAC Learning with Bandit Feedback: Sharp Sample Complexity in the Realizable Setting Algorithms with Polynomially-Improved Approximation Factors for the $2 \rightarrow q$ Norm, and Applications A computational phase transition for learning-to-sample from Ising models Covering vertices by sequential stars Fermi-Dirac machines as quantizations of neurons A Comprehensive Evaluation of Vertex Elimination Algorithms for Algorithmic Differentiation A Tight Bound on Localization of Electrical Flows Optimal Dimension-Free Sampling for Regularized Classification Reducing the Randomness in Partition Oracles for Bounded Degree Minor-Free Graphs Beyond the Half-Approximation: Fair and Efficient Online Class Matching Efficient Uniform Sampling of Surjections via their Profiles Tractable Maximization of Budgeted Phylogenetic Diversity on Networks Utilizing Node Scanwidth Fairness in Aggregation: Optimal Top-$k$ and Improved Full Ranking Learning-Augmented Online Scheduling with Parsimonious Preemption Entropy Equivalence Testing Lumberjack: Better Differentially Private Random Forests through Heavy Hitter Detection in Trees The Secretary Problem with a Stochastic Precursor Polynomial-Time Robust Multiclass Linear Classification under Gaussian Marginals Efficient Banzhaf-Based Data Valuation for $k$-Nearest Neighbors Classification Block-Sphere Vector Quantization An Approximation Algorithm for Graph Label Selection Iterative Chow Filtering for Learning with Distribution Shift Complexity of Non-Log-Concave Sampling in Fisher Information Stochastic Matching via Local Sparsification Finite Sample Bounds for Learning with Score Matching What is Learnable in Valiant's Theory of the Learnable? Provable Quantization with Randomized Hadamard Transform Min-Max Optimization Requires Exponentially Many Queries Fast and Compact Graph Cuts for the Boykov-Kolmogorov Algorithm A proximal gradient algorithm for composite log-concave sampling
Spanning Tree Covers for Path-Separable Graphs: Trading S...
[Submitted on 9 Nov 2025 (v1), last revised 28 Jul 2026 (this ve · 2025-11-09 · via cs.DS updates on arXiv.org

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Abstract:Given a graph $G=(V,E)$, a collection $\mathcal{T}$ of spanning trees of $G$ is called a spanning tree cover of stretch $\alpha$ if for every $u,v\in V$ there is a tree $T_{uv}\in\mathcal{T}$, such that \[d_{T_{uv}}(u,v)\leq\alpha\cdot d_G(u,v)~.\]
Spanning tree covers were introduced in the pioneering work of Gupta et al. [GKR04], that showed that $p$-path-separable graphs admit stretch-$3$ spanning tree covers with size $O(p\log n)$. Many subsequent papers focused on a relaxed notion of non-spanning tree covers, in which the trees are required to be dominating, but may use edges that do not belong to the graph. In particular, Bartal et al. [BFN22] devised a construction of non-spanning tree covers with stretch $1+\epsilon$ and size $O(p\cdot\frac{\log^2n}{\epsilon^2})$. Recently, for $K_r$-minor-free graphs, Chang et al. [CCL+23,CCL+24] devised a non-spanning tree cover with stretch $1+\epsilon$ and size $2^{\frac{1}{\epsilon}r^{O(r)}}$, and an exact spanning tree cover with size $r^{O(diam(G))}$. However, the problem of devising spanning tree covers with stretch smaller than $3$ and small size for general $p$-path-separable graphs remained open.
We show that $p$-path-separable graphs admit spanning tree covers with stretch $1+\epsilon$ and size $O(p\cdot\frac{\log^2n}{\epsilon})$. Moreover, we demonstrate that one can trade stretch for size, and devise spanning tree covers with stretch $O(k\log\log p)$ and size $O(kp^{\frac{1}{k}}\cdot\log^{2}n)$ for strongly $p$-path-separable graphs. We also provide a tradeoff for weakly path-separable graphs. For $K_r$-minor-free graphs, we devise spanning tree covers with stretch $O(k\log\log r)$ and size $O(kr^{2+\frac{1}{k}}\cdot\log^{2}n)$. For such graphs, it is only known that $p=r^{4602}$. Thus, for $r=\Omega(\log n)$ and $k\geq2$, this size is much smaller than that of our tree cover of stretch $1+\epsilon$.

Submission history

From: Idan Shabat [view email]
[v1] Sun, 9 Nov 2025 07:55:58 UTC (169 KB)
[v2] Tue, 28 Jul 2026 11:03:04 UTC (1,349 KB)