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cs.DS updates on arXiv.org

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
Improved Deterministic Distributed Construction of Spanners
Ofer Grossman, Merav Parter · 2017-08-03 · via cs.DS updates on arXiv.org

Graph spanners are fundamental graph structures with a wide range of applications in distributed networks. We consider a standard synchronous message passing model where in each round $O(\log n)$ bits can be transmitted over every edge (the CONGEST model). The state of the art of deterministic distributed spanner constructions suffers from large messages. The only exception is the work of Derbel et al. '10, which computes an optimal-sized $(2k-1)$-spanner but uses $O(n^{1-1/k})$ rounds. In this paper, we significantly improve this bound. We present a deterministic distributed algorithm that given an unweighted $n$-vertex graph $G = (V, E)$ and a parameter $k > 2$, constructs a $(2k-1)$-spanner with $O(k \cdot n^{1+1/k})$ edges within $O(2^{k} \cdot n^{1/2 - 1/k})$ rounds for every even $k$. For odd $k$, the number of rounds is $O(2^{k} \cdot n^{1/2 - 1/(2k)})$. For the weighted case, we provide the first deterministic construction of a $3$-spanner with $O(n^{3/2})$ edges that uses $O(\log n)$-size messages and $\widetilde{O}(1)$ rounds. If the nodes have IDs in $[1, Θ(n)]$, then the algorithm works in only $2$ rounds!