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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
A Polynomial Time Algorithm for Finding Area-Universal Re...
Jiun-Jie Wang · 2013-02-15 · via cs.DS updates on arXiv.org

A rectangular layout $\mathcal{L}$ is a rectangle partitioned into disjoint smaller rectangles so that no four smaller rectangles meet at the same point. Rectangular layouts were originally used as floorplans in VLSI design to represent VLSI chip layouts. More recently, they are used in graph drawing as rectangular cartograms. In these applications, an area $a(r)$ is assigned to each rectangle $r$, and the actual area of $r$ in $\mathcal{L}$ is required to be $a(r)$. Moreover, some applications require that we use combinatorially equivalent rectangular layouts to represent multiple area assignment functions. $\mathcal{L}$ is called {\em area-universal} if any area assignment to its rectangles can be realized by a layout that is combinatorially equivalent to $\mathcal{L}$. A basic question in this area is to determine if a given plane graph $G$ has an area-universal rectangular layout or not. A fixed-parameter-tractable algorithm for solving this problem was obtained in \cite{EMSV12}. Their algorithm takes $O(2^{O(K^2)}n^{O(1)})$ time (where $K$ is the maximum number of degree 4 vertices in any minimal separation component), which is exponential time in general case. It is an open problem to find a true polynomial time algorithm for solving this problem. In this paper, we describe such a polynomial time algorithm. This paper has been revised for many versions. For previous versions, referrers who are familiar with area-universal rectangular layouts always have the same doubt for the correctness of our algorithm. They doubt that our algorithm will give a wrong output which combine two \emph{conflicting} REL together. In the current version, we realize this critical issue for the previous algorithm and we will provide two subsections 5.3 and 5.4 to solve this issue. (A backtracking algorithm to detect wrong outputs.)