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

D
DataBreaches.Net
IT之家
IT之家
The Cloudflare Blog
Apple Machine Learning Research
Apple Machine Learning Research
WordPress大学
WordPress大学
N
Netflix TechBlog - Medium
阮一峰的网络日志
阮一峰的网络日志
P
Proofpoint News Feed
L
LangChain Blog
博客园 - Franky
美团技术团队
J
Java Code Geeks
Microsoft Security Blog
Microsoft Security Blog
博客园 - 叶小钗
小众软件
小众软件
Y
Y Combinator Blog
B
Blog RSS Feed
Cyber Security Advisories - MS-ISAC
Cyber Security Advisories - MS-ISAC
D
Docker
Hugging Face - Blog
Hugging Face - Blog
Jina AI
Jina AI
罗磊的独立博客
大猫的无限游戏
大猫的无限游戏
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
Optimal Aggregation Algorithms for Middleware
Ron Fagin, Amnon Lotem, Moni Naor · 2002-04-23 · via cs.DS updates on arXiv.org

Let D be a database of N objects where each object has m fields. The objects are given in m sorted lists (where the ith list is sorted according to the ith field). Our goal is to find the top k objects according to a monotone aggregation function t, while minimizing access to the lists. The problem arises in several contexts. In particular Fagin (JCSS 1999) considered it for the purpose of aggregating information in a multimedia database system. We are interested in instance optimality, i.e. that our algorithm will be as good as any other (correct) algorithm on any instance. We provide and analyze several instance optimal algorithms for the task, with various access costs and models.