1,276 research outputs found

    LIPIcs, Volume 251, ITCS 2023, Complete Volume

    Get PDF
    LIPIcs, Volume 251, ITCS 2023, Complete Volum

    (Almost) Ruling Out SETH Lower Bounds for All-Pairs Max-Flow

    Full text link
    The All-Pairs Max-Flow problem has gained significant popularity in the last two decades, and many results are known regarding its fine-grained complexity. Despite this, wide gaps remain in our understanding of the time complexity for several basic variants of the problem. In this paper, we aim to bridge this gap by providing algorithms, conditional lower bounds, and non-reducibility results. Our main result is that for most problem settings, deterministic reductions based on the Strong Exponential Time Hypothesis (SETH) cannot rule out n4−o(1)n^{4-o(1)} time algorithms under a hypothesis called NSETH. In particular, to obtain our result for the setting of undirected graphs with unit node-capacities, we design a new randomized O(m2+o(1))O(m^{2+o(1)}) time combinatorial algorithm, improving on the recent O(m11/5+o(1))O(m^{11/5+o(1)}) time algorithm [Huang et al., STOC 2023] and matching their m2−o(1)m^{2-o(1)} lower bound (up to subpolynomial factors), thus essentially settling the time complexity for this setting of the problem. More generally, our main technical contribution is the insight that stst-cuts can be verified quickly, and that in most settings, stst-flows can be shipped succinctly (i.e., with respect to the flow support). This is a key idea in our non-reducibility results, and it may be of independent interest

    Spectral Sparsification for Communication-Efficient Collaborative Rotation and Translation Estimation

    Full text link
    We propose fast and communication-efficient optimization algorithms for multi-robot rotation averaging and translation estimation problems that arise from collaborative simultaneous localization and mapping (SLAM), structure-from-motion (SfM), and camera network localization applications. Our methods are based on theoretical relations between the Hessians of the underlying Riemannian optimization problems and the Laplacians of suitably weighted graphs. We leverage these results to design a collaborative solver in which robots coordinate with a central server to perform approximate second-order optimization, by solving a Laplacian system at each iteration. Crucially, our algorithms permit robots to employ spectral sparsification to sparsify intermediate dense matrices before communication, and hence provide a mechanism to trade off accuracy with communication efficiency with provable guarantees. We perform rigorous theoretical analysis of our methods and prove that they enjoy (local) linear rate of convergence. Furthermore, we show that our methods can be combined with graduated non-convexity to achieve outlier-robust estimation. Extensive experiments on real-world SLAM and SfM scenarios demonstrate the superior convergence rate and communication efficiency of our methods.Comment: Revised extended technical report (37 pages, 15 figures, 6 tables

    Multi Layer Peeling for Linear Arrangement and Hierarchical Clustering

    Get PDF
    We present a new multi-layer peeling technique to cluster points in a metric space. A well-known non-parametric objective is to embed the metric space into a simpler structured metric space such as a line (i.e., Linear Arrangement) or a binary tree (i.e., Hierarchical Clustering). Points which are close in the metric space should be mapped to close points/leaves in the line/tree; similarly, points which are far in the metric space should be far in the line or on the tree. In particular we consider the Maximum Linear Arrangement problem [Refael Hassin and Shlomi Rubinstein, 2001] and the Maximum Hierarchical Clustering problem [Vincent Cohen-Addad et al., 2018] applied to metrics. We design approximation schemes (1-? approximation for any constant ? > 0) for these objectives. In particular this shows that by considering metrics one may significantly improve former approximations (0.5 for Max Linear Arrangement and 0.74 for Max Hierarchical Clustering). Our main technique, which is called multi-layer peeling, consists of recursively peeling off points which are far from the "core" of the metric space. The recursion ends once the core becomes a sufficiently densely weighted metric space (i.e. the average distance is at least a constant times the diameter) or once it becomes negligible with respect to its inner contribution to the objective. Interestingly, the algorithm in the Linear Arrangement case is much more involved than that in the Hierarchical Clustering case, and uses a significantly more delicate peeling

    Efficient 1-Laplacian Solvers for Well-Shaped Simplicial Complexes: Beyond Betti Numbers and Collapsing Sequences

    Get PDF
    We present efficient algorithms for solving systems of linear equations in 1-Laplacians of well-shaped simplicial complexes. 1-Laplacians, or higher-dimensional Laplacians, generalize graph Laplacians to higher-dimensional simplicial complexes and play a key role in computational topology and topological data analysis. Previously, nearly-linear time solvers were developed for simplicial complexes with known collapsing sequences and bounded Betti numbers, such as those triangulating a three-ball in R3 (Cohen, Fasy, Miller, Nayyeri, Peng, and Walkington [SODA’2014], Black, Maxwell, Nayyeri, and Winkelman [SODA’2022], Black and Nayyeri [ICALP’2022]). Furthermore, Nested Dissection provides quadratic time solvers for more general systems with nonzero structures representing well-shaped simplicial complexes embedded in R3. We generalize the specialized solvers for 1-Laplacians to simplicial complexes with additional geometric structures but without collapsing sequences and bounded Betti numbers, and we improve the runtime of Nested Dissection. We focus on simplicial complexes that meet two conditions: (1) each individual simplex has a bounded aspect ratio, and (2) they can be divided into “disjoint” and balanced regions with well-shaped interiors and boundaries. Our solvers draw inspiration from the Incomplete Nested Dissection for stiffness matrices of well-shaped trusses (Kyng, Peng, Schwieterman, and Zhang [STOC’2018]).ISSN:1868-896

    Product structure of graph classes with strongly sublinear separators

    Full text link
    We investigate the product structure of hereditary graph classes admitting strongly sublinear separators. We characterise such classes as subgraphs of the strong product of a star and a complete graph of strongly sublinear size. In a more precise result, we show that if any hereditary graph class G\mathcal{G} admits O(n1−ϔ)O(n^{1-\epsilon}) separators, then for any fixed Ύ∈(0,Ï”)\delta\in(0,\epsilon) every nn-vertex graph in G\mathcal{G} is a subgraph of the strong product of a graph HH with bounded tree-depth and a complete graph of size O(n1−ϔ+ÎŽ)O(n^{1-\epsilon+\delta}). This result holds with ÎŽ=0\delta=0 if we allow HH to have tree-depth O(log⁥log⁥n)O(\log\log n). Moreover, using extensions of classical isoperimetric inequalties for grids graphs, we show the dependence on ÎŽ\delta in our results and the above td(H)∈O(log⁥log⁥n)\text{td}(H)\in O(\log\log n) bound are both best possible. We prove that nn-vertex graphs of bounded treewidth are subgraphs of the product of a graph with tree-depth tt and a complete graph of size O(n1/t)O(n^{1/t}), which is best possible. Finally, we investigate the conjecture that for any hereditary graph class G\mathcal{G} that admits O(n1−ϔ)O(n^{1-\epsilon}) separators, every nn-vertex graph in G\mathcal{G} is a subgraph of the strong product of a graph HH with bounded tree-width and a complete graph of size O(n1−ϔ)O(n^{1-\epsilon}). We prove this for various classes G\mathcal{G} of interest.Comment: v2: added bad news subsection; v3: removed section "Polynomial Expansion Classes" which had an error, added section "Lower Bounds", and added a new author; v4: minor revisions and corrections

    Algorithms for Geometric Facility Location: Centers in a Polygon and Dispersion on a Line

    Get PDF
    We study three geometric facility location problems in this thesis. First, we consider the dispersion problem in one dimension. We are given an ordered list of (possibly overlapping) intervals on a line. We wish to choose exactly one point from each interval such that their left to right ordering on the line matches the input order. The aim is to choose the points so that the distance between the closest pair of points is maximized, i.e., they must be socially distanced while respecting the order. We give a new linear-time algorithm for this problem that produces a lexicographically optimal solution. We also consider some generalizations of this problem. For the next two problems, the domain of interest is a simple polygon with n vertices. The second problem concerns the visibility center. The convention is to think of a polygon as the top view of a building (or art gallery) where the polygon boundary represents opaque walls. Two points in the domain are visible to each other if the line segment joining them does not intersect the polygon exterior. The distance to visibility from a source point to a target point is the minimum geodesic distance from the source to a point in the polygon visible to the target. The question is: Where should a single guard be located within the polygon to minimize the maximum distance to visibility? For m point sites in the polygon, we give an O((m + n) log (m + n)) time algorithm to determine their visibility center. Finally, we address the problem of locating the geodesic edge center of a simple polygon—a point in the polygon that minimizes the maximum geodesic distance to any edge. For a triangle, this point coincides with its incenter. The geodesic edge center is a generalization of the well-studied geodesic center (a point that minimizes the maximum distance to any vertex). Center problems are closely related to farthest Voronoi diagrams, which are well- studied for point sites in the plane, and less well-studied for line segment sites in the plane. When the domain is a polygon rather than the whole plane, only the case of point sites has been addressed—surprisingly, more general sites (with line segments being the simplest example) have been largely ignored. En route to our solution, we revisit, correct, and generalize (sometimes in a non-trivial manner) existing algorithms and structures tailored to work specifically for point sites. We give an optimal linear-time algorithm for finding the geodesic edge center of a simple polygon

    Thick Forests

    Full text link
    We consider classes of graphs, which we call thick graphs, that have their vertices replaced by cliques and their edges replaced by bipartite graphs. In particular, we consider the case of thick forests, which are a subclass of perfect graphs. We show that this class can be recognised in polynomial time, and examine the complexity of counting independent sets and colourings for graphs in the class. We consider some extensions of our results to thick graphs beyond thick forests.Comment: 40 pages, 19 figure

    Clique‐width: Harnessing the power of atoms

    Get PDF
    Many NP-complete graph problems are polynomial-time solvable on graph classes of bounded clique-width. Several of these problems are polynomial-time solvable on a hereditary graph class if they are so on the atoms (graphs with no clique cut-set) of . Hence, we initiate a systematic study into boundedness of clique-width of atoms of hereditary graph classes. A graph is -free if is not an induced subgraph of , and it is -free if it is both -free and -free. A class of -free graphs has bounded clique-width if and only if its atoms have this property. This is no longer true for -free graphs, as evidenced by one known example. We prove the existence of another such pair and classify the boundedness of clique-width on -free atoms for all but 18 cases

    Fast Algorithms for Separable Linear Programs

    Full text link
    In numerical linear algebra, considerable effort has been devoted to obtaining faster algorithms for linear systems whose underlying matrices exhibit structural properties. A prominent success story is the method of generalized nested dissection~[Lipton-Rose-Tarjan'79] for separable matrices. On the other hand, the majority of recent developments in the design of efficient linear program (LP) solves do not leverage the ideas underlying these faster linear system solvers nor consider the separable structure of the constraint matrix. We give a faster algorithm for separable linear programs. Specifically, we consider LPs of the form min⁥Ax=b,l≀x≀uc⊀x\min_{\mathbf{A}\mathbf{x}=\mathbf{b}, \mathbf{l}\leq\mathbf{x}\leq\mathbf{u}} \mathbf{c}^\top\mathbf{x}, where the graphical support of the constraint matrix A∈Rn×m\mathbf{A} \in \mathbb{R}^{n\times m} is O(nα)O(n^\alpha)-separable. These include flow problems on planar graphs and low treewidth matrices among others. We present an O~((m+m1/2+2α)log⁥(1/Ï”))\tilde{O}((m+m^{1/2 + 2\alpha}) \log(1/\epsilon)) time algorithm for these LPs, where Ï”\epsilon is the relative accuracy of the solution. Our new solver has two important implications: for the kk-multicommodity flow problem on planar graphs, we obtain an algorithm running in O~(k5/2m3/2)\tilde{O}(k^{5/2} m^{3/2}) time in the high accuracy regime; and when the support of A\mathbf{A} is O(nα)O(n^\alpha)-separable with α≀1/4\alpha \leq 1/4, our algorithm runs in O~(m)\tilde{O}(m) time, which is nearly optimal. The latter significantly improves upon the natural approach of combining interior point methods and nested dissection, whose time complexity is lower bounded by Ω(m(m+mαω))=Ω(m3/2)\Omega(\sqrt{m}(m+m^{\alpha\omega}))=\Omega(m^{3/2}), where ω\omega is the matrix multiplication constant. Lastly, in the setting of low-treewidth LPs, we recover the results of [DLY,STOC21] and [GS,22] with significantly simpler data structure machinery.Comment: 55 pages. To appear at SODA 202
    • 

    corecore