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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
Fault Tolerant Approximate BFS Structures
Merav Parter, David Peleg · 2014-06-24 · via cs.DS updates on arXiv.org

This paper addresses the problem of designing a {\em fault-tolerant} $(α, β)$ approximate BFS structure (or {\em FT-ABFS structure} for short), namely, a subgraph $H$ of the network $G$ such that subsequent to the failure of some subset $F$ of edges or vertices, the surviving part of $H$ still contains an \emph{approximate} BFS spanning tree for (the surviving part of) $G$, satisfying $dist(s,v,H\setminus F) \leq α\cdot dist(s,v,G\setminus F)+β$ for every $v \in V$. We first consider {\em multiplicative} $(α,0)$ FT-ABFS structures resilient to a failure of a single edge and present an algorithm that given an $n$-vertex unweighted undirected graph $G$ and a source $s$ constructs a $(3,0)$ FT-ABFS structure rooted at $s$ with at most $4n$ edges (improving by an $O(\log n)$ factor on the near-tight result of \cite{BS10} for the special case of edge failures). Assuming at most $f$ edge failures, for constant integer $f>1$, we prove that there exists a (poly-time constructible) $(3(f+1), (f+1) \log n)$ FT-ABFS structure with $O(f n)$ edges. We then consider {\em additive} $(1,β)$ FT-ABFS structures. In contrast to the linear size of $(α,0)$ FT-ABFS structures, we show that for every $β\in [1, O(\log n)]$ there exists an $n$-vertex graph $G$ with a source $s$ for which any $(1,β)$ FT-ABFS structure rooted at $s$ has $Ω(n^{1+ε(β)})$ edges, for some function $ε(β) \in (0,1)$. In particular, $(1,3)$ FT-ABFS structures admit a lower bound of $Ω(n^{5/4})$ edges. Our lower bounds are complemented by an upper bound, showing that there exists a poly-time algorithm that for every $n$-vertex unweighted undirected graph $G$ and source $s$ constructs a $(1,4)$ FT-ABFS structure rooted at $s$ with at most $O(n^{4/3})$ edges.