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

Martin Fowler
Martin Fowler
Engineering at Meta
Engineering at Meta
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
阮一峰的网络日志
阮一峰的网络日志
奇客Solidot–传递最新科技情报
奇客Solidot–传递最新科技情报
量子位
Jina AI
Jina AI
Microsoft Azure Blog
Microsoft Azure Blog
博客园_首页
L
LangChain Blog
A
About on SuperTechFans
人人都是产品经理
人人都是产品经理
freeCodeCamp Programming Tutorials: Python, JavaScript, Git & More
美团技术团队
博客园 - 三生石上(FineUI控件)
N
Netflix TechBlog - Medium
D
DataBreaches.Net
P
Proofpoint News Feed
小众软件
小众软件
Vercel News
Vercel News
T
The Blog of Author Tim Ferriss
WordPress大学
WordPress大学
雷峰网
雷峰网
G
Google Developers Blog

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
Capacity-Insensitive Algorithms for Online Facility Assig...
Tsubasa Harada, Toshiya Itoh, Shuichi Miyazaki · 2022-07-12 · via cs.DS updates on arXiv.org

In the online facility assignment problem OFA(k,\ell), there exist k servers with a capacity \ell \geq 1 on a metric space and a request arrives one-by-one. The task of an online algorithm is to irrevocably match a current request with one of the servers with vacancies before the next request arrives. As special cases for OFA(k,\ell), we consider OFA(k,\ell) on a line, which is denoted by OFAL(k,\ell) and OFAL_{eq}(k,\ell), where the latter is the case of OFAL(k,\ell) with equidistant servers. In this paper, we deal with the competitive analysis for the above problems. As a natural generalization of the greedy algorithm GRDY, we introduce a class of algorithms called MPFS (most preferred free servers) and show that any MPFS algorithm has the capacity-insensitive property, i.e., for any \ell \geq 1, ALG is c-competitive for OFA(k,1) iff ALG is c-competitive for OFA(k,\ell). By applying the capacity-insensitive property of the greedy algorithm GRDY, we derive the matching upper and lower bounds 4k-5 on the competitive ratio of GRDY for OFAL_{eq}(k,\ell). To investigate the capability of MPFS algorithms, we show that the competitive ratio of any MPFS algorithm ALG for OFAL_{eq}(k,\ell) is at least $2k-1$. Then we propose a new MPFS algorithm IDAS (Interior Division for Adjacent Servers) for OFAL(k,\ell) and show that the competitive ratio of IDAS for OFAL}_{eq}(k,\ell) is at most 2k-1, i.e., IDAS for OFAL_{eq}(k,\ell) is best possible in all the MPFS algorithms.