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
Martin Fowler
Martin Fowler
MongoDB | Blog
MongoDB | Blog
Engineering at Meta
Engineering at Meta
Stack Overflow Blog
Stack Overflow Blog
Google DeepMind News
Google DeepMind News
Microsoft Security Blog
Microsoft Security Blog
aimingoo的专栏
aimingoo的专栏
I
InfoQ
B
Blog
WordPress大学
WordPress大学
Jina AI
Jina AI
小众软件
小众软件
OSCHINA 社区最新新闻
OSCHINA 社区最新新闻
博客园_首页
奇客Solidot–传递最新科技情报
奇客Solidot–传递最新科技情报
酷 壳 – CoolShell
酷 壳 – CoolShell
阮一峰的网络日志
阮一峰的网络日志
Cyber Security Advisories - MS-ISAC
Cyber Security Advisories - MS-ISAC
G
Google Developers Blog
C
Check Point Blog
月光博客
月光博客
L
LangChain Blog
GbyAI
GbyAI

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
Finding All Leftmost Separators of Size $\leq k$
Mahdi Belbasi, Martin Fürer · 2021-11-04 · via cs.DS updates on arXiv.org

We define a notion called leftmost separator of size at most $k$. A leftmost separator of size $k$ is a minimal separator $S$ that separates two given sets of vertices $X$ and $Y$ such that we "cannot move $S$ more towards $X$" such that $|S|$ remains smaller than the threshold. One of the incentives is that by using leftmost separators we can improve the time complexity of treewidth approximation. Treewidth approximation is a problem which is known to have a linear time FPT algorithm in terms of input size, and only single exponential in terms of the parameter, treewidth. It is not known whether this result can be improved theoretically. However, the coefficient of the parameter $k$ (the treewidth) in the exponent is large. Hence, our goal is to decrease the coefficient of $k$ in the exponent, in order to achieve a more practical algorithm. Hereby, we trade a linear-time algorithm for an $\mathcal{O}(n \log n)$-time algorithm. The previous known $\mathcal{O}(f(k) n \log n)$-time algorithms have dependences of $2^{24k}k!$, $2^{8.766k}k^2$ (a better analysis shows that it is $2^{7.671k}k^2$), and higher. In this paper, we present an algorithm for treewidth approximation which runs in time $\mathcal{O}(2^{6.755k}\ n \log n)$, Furthermore, we count the number of leftmost separators and give a tight upper bound for them. We show that the number of leftmost separators of size $\leq k$ is at most $C_{k-1}$ (Catalan number). Then, we present an algorithm which outputs all leftmost separators in time $\mathcal{O}(\frac{4^k}{\sqrt{k}}n)$.