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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
Balancing Degree, Diameter and Weight in Euclidean Spanners
Shay Solomon, Michael Elkin · 2011-08-31 · via cs.DS updates on arXiv.org

In this paper we devise a novel \emph{unified} construction of Euclidean spanners that trades between the maximum degree, diameter and weight gracefully. For a positive integer k, our construction provides a (1+eps)-spanner with maximum degree O(k), diameter O(log_k n + alpha(k)), weight O(k \cdot log_k n \cdot log n) \cdot w(MST(S)), and O(n) edges. Note that for k= n^{1/alpha(n)} this gives rise to diameter O(alpha(n)), weight O(n^{1/alpha(n)} \cdot log n \cdot alpha(n)) \cdot w(MST(S)) and maximum degree O(n^{1/alpha(n)}), which improves upon a classical result of Arya et al. \cite{ADMSS95}; in the corresponding result from \cite{ADMSS95} the spanner has the same number of edges and diameter, but its weight and degree may be arbitrarily large. Also, for k = O(1) this gives rise to maximum degree O(1), diameter O(log n) and weight O(log^2 n) \cdot w(MST(S)), which reproves another classical result of Arya et al. \cite{ADMSS95}. Our bound of O(log_k n + alpha(k)) on the diameter is optimal under the constraints that the maximum degree is O(k) and the number of edges is O(n). Our bound on the weight is optimal up to a factor of log n. Our construction also provides a similar tradeoff in the complementary range of parameters, i.e., when the weight should be smaller than log^2 n, but the diameter is allowed to grow beyond log n. For random point sets in the d-dimensional unit cube, we "shave" a factor of log n from the weight bound. Specifically, in this case our construction achieves maximum degree O(k), diameter O(log_k n + alpha(k)) and weight that is with high probability O(k \cdot log_k n) \cdot w(MST(S)). Finally, en route to these results we devise optimal constructions of 1-spanners for general tree metrics, which are of independent interest.