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

Recent Announcements
Recent Announcements
爱范儿
爱范儿
freeCodeCamp Programming Tutorials: Python, JavaScript, Git & More
宝玉的分享
宝玉的分享
T
Tailwind CSS Blog
博客园_首页
IT之家
IT之家
OSCHINA 社区最新新闻
OSCHINA 社区最新新闻
博客园 - 三生石上(FineUI控件)
有赞技术团队
有赞技术团队
大猫的无限游戏
大猫的无限游戏
雷峰网
雷峰网
奇客Solidot–传递最新科技情报
奇客Solidot–传递最新科技情报
博客园 - 司徒正美
WordPress大学
WordPress大学
Last Week in AI
Last Week in AI
人人都是产品经理
人人都是产品经理
Jina AI
Jina AI
月光博客
月光博客
小众软件
小众软件
S
SegmentFault 最新的问题
量子位
阮一峰的网络日志
阮一峰的网络日志
钛媒体:引领未来商业与生活新知
钛媒体:引领未来商业与生活新知

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 Distance (Sensitivity) Oracles with Subquadratic...
Davide Bilò, Shiri Chechik, Keerti Choudhary, Sarel Cohen, Tobia · 2024-08-19 · via cs.DS updates on arXiv.org

A distance oracle (DO) with stretch $(α, β)$ for a graph $G$ is a data structure that, when queried with vertices $s$ and $t$, returns a value $\widehat{d}(s,t)$ such that $d(s,t) \le \widehat{d}(s,t) \le α\cdot d(s,t) + β$. An $f$-edge fault-tolerant distance sensitivity oracle ($f$-DSO) additionally receives a set $F$ of up to $f$ edges and estimates the $s$-$t$-distance in $G{-}F$. Our first contribution is a new distance oracle with subquadratic space for undirected graphs. Introducing a small additive stretch $β> 0$ allows us to make the multiplicative stretch $α$ arbitrarily small. This sidesteps a known lower bound of $α\ge 3$ (for $β= 0$ and subquadratic space) [Thorup & Zwick, JACM 2005]. We present a DO for graphs with edge weights in $[0,W]$ that, for any positive integer $t$ and any $c \in (0, \ell/2]$, has stretch $(1{+}\frac{1}{\ell}, 2W)$, space $\widetilde{O}(n^{2-\frac{c}{t}})$, and query time $O(n^c)$. These are the first subquadratic-space DOs with $(1+ε, O(1))$-stretch generalizing Agarwal and Godfrey's results for sparse graphs [SODA 2013] to general undirected graphs. Our second contribution is a framework that turns a $(α,β)$-stretch DO for unweighted graphs into an $(α(1{+}\varepsilon),β)$-stretch $f$-DSO with sensitivity $f = o(\log(n)/\log\log n)$ and retains subquadratic space. This generalizes a result by Bilò, Chechik, Choudhary, Cohen, Friedrich, Krogmann, and Schirneck [STOC 2023, TheoretiCS 2024] for the special case of stretch $(3,0)$ and $f = O(1)$. By combining the framework with our new distance oracle, we obtain an $f$-DSO that, for any $γ\in (0, (\ell{+}1)/2]$, has stretch $((1{+}\frac{1}{\ell}) (1{+}\varepsilon), 2)$, space $n^{ 2- \fracγ{(\ell+1)(f+1)} + o(1)}/\varepsilon^{f+2}$, and query time $\widetilde{O}(n^γ /{\varepsilon}^2)$.