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

IT之家
IT之家
Engineering at Meta
Engineering at Meta
腾讯CDC
宝玉的分享
宝玉的分享
H
Help Net Security
I
InfoQ
博客园 - Franky
The GitHub Blog
The GitHub Blog
奇客Solidot–传递最新科技情报
奇客Solidot–传递最新科技情报
H
Hackread – Cybersecurity News, Data Breaches, AI and More
Microsoft Security Blog
Microsoft Security Blog
M
MIT News - Artificial intelligence
博客园_首页
美团技术团队
Recent Announcements
Recent Announcements
freeCodeCamp Programming Tutorials: Python, JavaScript, Git & More
雷峰网
雷峰网
The Cloudflare Blog
博客园 - 司徒正美
Vercel News
Vercel News
MyScale Blog
MyScale Blog
人人都是产品经理
人人都是产品经理
爱范儿
爱范儿
月光博客
月光博客

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
Triangle-free 2-matchings
Katarzyna Paluch · 2023-11-23 · via cs.DS updates on arXiv.org

We consider the problem of finding a maximum size triangle-free $2$-matching in a graph $G=(V,E)$. A (simple) $2$-matching is any subset of the edges such that each vertex is incident to at most two edges from the subset. The first polynomial time algorithm for this problem was given by Hartvigsen in 1984 in his PhD thesis and its improved version has been recently published in a journal. We present a different, significantly simpler algorithm with a relatively short proof of correctness. Our algorithm with running time $O(|V||E|)$ is additionally faster than the one by Hartvigsen having running time $O(|V|^3|E|^2)$. It has been proven before that for any triangle-free $2$-matching $M$ which is not maximum the graph contains an $M$-augmenting path, whose application to $M$ results in a bigger triangle-free $2$-matching. A new observation is that the search for an augmenting path $P$ can be restricted to so-called {\em amenable} paths that go through any triangle $t$ contained in $P\cup M$ a limited number of times. Amenable paths can be characterised with the aid of {\em half-edges}. A {\em half-edge} of edge $e$ is, informally speaking, a half of $e$ containing exactly one of its endpoints. Each half-edge serves also as a {\em hinge} - a connector between one pair of edges on an alternating path. To find an amenable augmenting path we thus dynamically remove and re-add half-edges to forbid or allow some edges to be followed by certain others. The existence of amenable augmenting paths follows from our decomposition theorem for triangle-free $2$-matchings. This decomposition theorem is largely the same as the decomposition from versions 1-6 of this paper and is moreover simpler and stronger than the one given by Kobayashi and Noguchi.