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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
Transitive-Closure Spanners
Arnab Bhattacharyya, Elena Grigorescu, Kyomin Jung, Sofya Raskho · 2008-08-13 · via cs.DS updates on arXiv.org

Given a directed graph G = (V,E) and an integer k>=1, a k-transitive-closure-spanner (k-TC-spanner) of G is a directed graph H = (V, E_H) that has (1) the same transitive-closure as G and (2) diameter at most k. These spanners were implicitly studied in access control, data structures, and property testing, and properties of these spanners have been rediscovered over the span of 20 years. The main goal in each of these applications is to obtain the sparsest k-TC-spanners. We bring these diverse areas under the unifying framework of TC-spanners. We initiate the study of approximability of the size of the sparsest k-TC-spanner for a given directed graph. We completely resolve the approximability of 2-TC-spanners, showing that it is Theta(log n) unless P = NP. For k>2, we present a polynomial-time algorithm that finds a k-TC-spanner with size within O((n log n)^{1-1/k}) of the optimum. Our algorithmic techniques also yield algorithms with the best-known approximation ratio for well-studied problems on directed spanners when k>3: DIRECTED k-SPANNER, CLIENT/SERVER DIRECTED k-SPANNER, and k-DIAMETER SPANNING SUBGRAPH. For constant k>=3, we show that the size of the sparsest k-TC-spanner is hard to approximate with 2^{log^{1-eps} n} ratio unless NP \subseteq DTIME(n^{polylog n}}). Finally, we study the size of the sparsest k-TC-spanners for H-minor-free graph families. Combining our constructions with our insight that 2-TC-spanners can be used for designing property testers, we obtain a monotonicity tester with O(log^2 n /eps) queries for any poset whose transitive reduction is an H-minor free digraph, improving the Theta(sqrt(n) log n/eps)-queries required of the tester due to Fischer et al (2002).