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

量子位
Recent Announcements
Recent Announcements
D
Docker
V
V2EX
阮一峰的网络日志
阮一峰的网络日志
Vercel News
Vercel News
Microsoft Security Blog
Microsoft Security Blog
The GitHub Blog
The GitHub Blog
U
Unit 42
奇客Solidot–传递最新科技情报
奇客Solidot–传递最新科技情报
月光博客
月光博客
腾讯CDC
B
Blog
博客园_首页
罗磊的独立博客
D
DataBreaches.Net
IT之家
IT之家
酷 壳 – CoolShell
酷 壳 – CoolShell
L
LangChain Blog
aimingoo的专栏
aimingoo的专栏
MongoDB | Blog
MongoDB | Blog
GbyAI
GbyAI
Stack Overflow Blog
Stack Overflow Blog
M
MIT News - Artificial intelligence

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
Distance-preserving Subgraphs of Interval Graphs
Kshitij Gajjar, Jaikumar Radhakrishnan · 2017-08-10 · via cs.DS updates on arXiv.org

We consider the problem of finding small distance-preserving subgraphs of undirected, unweighted interval graphs with $k$ terminal vertices. To start with, we show that finding an optimal distance-preserving subgraph is $\mathsf{NP}$-hard for general graphs. Then, we show that every interval graph admits a subgraph with $O(k)$ branching vertices that approximates pairwise terminal distances up to an additive term of $+1$. We also present an interval graph $G_{\mathrm{int}}$ for which the $+1$ approximation is necessary to obtain the $O(k)$ upper bound on the number of branching vertices. In particular, any distance-preserving subgraph of $G_{\mathrm{int}}$ has $Ω(k\log k)$ branching vertices. Furthermore, we prove that every interval graph admits a distance-preserving subgraph with $O(k\log k)$ branching vertices, implying that the $Ω(k\log k)$ lower bound for interval graphs is tight. To conclude, we show that there exists an interval graph such that every optimal distance-preserving subgraph of it has $O(k)$ branching vertices and $Ω(k\log k)$ branching edges, thereby providing a separation between branching vertices and branching edges. The $O(k)$ bound for distance-approximating subgraphs follows from a naïve analysis of shortest paths in interval graphs. $G_{\mathrm{int}}$ is constructed using bit-reversal permutation matrices. The $O(k\log k)$ bound for distance-preserving subgraphs uses a divide-and-conquer approach. Finally, the separation between branching vertices and branching edges employs Hansel's lemma for graph covering.