惯性聚合 高效追踪和阅读你感兴趣的博客、新闻、科技资讯
阅读原文 在惯性聚合中打开

推荐订阅源

Last Week in AI
Last Week in AI
U
Unit 42
博客园 - 【当耐特】
Y
Y Combinator Blog
H
Hackread – Cybersecurity News, Data Breaches, AI and More
Microsoft Security Blog
Microsoft Security Blog
Recent Announcements
Recent Announcements
P
Proofpoint News Feed
Martin Fowler
Martin Fowler
量子位
让小产品的独立变现更简单 - ezindie.com
让小产品的独立变现更简单 - ezindie.com
有赞技术团队
有赞技术团队
aimingoo的专栏
aimingoo的专栏
博客园 - 司徒正美
美团技术团队
雷峰网
雷峰网
小众软件
小众软件
G
Google Developers Blog
GbyAI
GbyAI
Jina AI
Jina AI
爱范儿
爱范儿
奇客Solidot–传递最新科技情报
奇客Solidot–传递最新科技情报
F
Fortinet All Blogs
Vercel News
Vercel News

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
Generic Single Edge Fault Tolerant Exact Distance Oracle
Manoj Gupta, Aditi Singh · 2018-05-01 · via cs.DS updates on arXiv.org

Given an undirected unweighted graph $G$ and a source set $S$ of $|S| = σ$ sources, we want to build a data structure which can process the following query {\sc Q}$(s,t,e):$ find the shortest distance from $s$ to $t$ avoiding an edge $e$, where $s \in S$ and $t \in V$. When $σ=n$, Demetrescu, Thorup, Chowdhury and Ramachandran (SIAM Journal of Computing, 2008) designed an algorithm with $\tilde O(n^2)$ space ($\tilde O(\cdot)$ hides poly $\log n$ factor.) and $O(1)$ query time. A natural open question is to generalize this result to any number of sources. Recently, Bil{ò} et. al. (STACS 2018) designed a data-structure of size $\tilde O(σ^{1/2}n^{3/2})$ with the query time of $O(\sqrt{nσ})$ for the above problem. We improve their result by designing a data-structure of size $\tilde O(σ^{1/2} n^{3/2})$ that can answer queries in $\tilde O(1)$ time. In a related problem of finding fault tolerant subgraph, Parter and Peleg (ESA 2013) showed that if detours of the {\em replacement} paths ending at a vertex $t$ are disjoint, then the number of such paths is $O(\sqrt{nσ})$. This eventually gives a bound of $O( n \sqrt{n σ}) = O(σ^{1/2}n^{3/2})$ for their problem. {\em Disjointness of detours} is a very crucial property used in the above result. We show a similar result for a subset of replacement path which \textbf{may not} be disjoint. This result is the crux of our paper and may be of independent interest.?