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In this paper we revisit the well known set-maxima problem in the oblivious setting. Let $X=\{x_1,\ldots, x_n\}$ be a set of $n$ elements with an underlying total order. Let $\mathcal{S}=\{S_1,\ldots,S_m\}$ be a collection of $m$ distinct…

Data Structures and Algorithms · Computer Science 2021-07-02 Avah Banerjee , Dana Richards

Consider an ergodic unimodular random one-ended planar graph $\G$ of finite expected degree. We prove that it has an isometry-invariant locally finite embedding in the Euclidean plane if and only if it is invariantly amenable. By "locally…

Probability · Mathematics 2021-10-27 Itai Benjamini , Adam Timar

The objective of ordinal embedding is to find a Euclidean representation of a set of abstract items, using only answers to triplet comparisons of the form "Is item $i$ closer to the item $j$ or item $k$?". In recent years, numerous…

Machine Learning · Computer Science 2021-10-22 Leena Chennuru Vankadara , Siavash Haghiri , Michael Lohaus , Faiz Ul Wahab , Ulrike von Luxburg

We study embeddings of continuous dynamical systems in larger dimensions via projector operators. We call this technique PEDS, projective embedding of dynamical systems, as the stable fixed point of the dynamics are recovered via projection…

Dynamical Systems · Mathematics 2023-10-19 Francesco Caravelli , Fabio L. Traversa , Michele Bonnin , Fabrizio Bonani

The {\sc Directed Maximum Leaf Out-Branching} problem is to find an out-branching (i.e. a rooted oriented spanning tree) in a given digraph with the maximum number of leaves. In this paper, we improve known parameterized algorithms and…

Data Structures and Algorithms · Computer Science 2007-07-10 Noga Alon , Fedor V. Fomin , Gregory Gutin , Michael Krivelevich , Saket Saurabh

We consider the problem of constructing embeddings of large attributed graphs and supporting multiple downstream learning tasks. We develop a graph embedding method, which is based on extending deep metric and unbiased contrastive learning…

Machine Learning · Computer Science 2024-11-22 Xiang Li , Gagan Agrawal , Ruoming Jin , Rajiv Ramnath

This note considers the maximal positively invariant set for polynomial discrete time dynamics subject to constraints specified by a basic semialgebraic set. The note utilizes a relatively direct, but apparently overlooked, fact stating…

Dynamical Systems · Mathematics 2017-12-05 Saša V. Raković , Mario E. Villanueva

The convex hull of a planar point set is the smallest convex polygon containing each point in the set. The dynamic convex hull problem concerns efficiently maintaining the convex hull of a set of points subject to additions and removals.…

Distributed, Parallel, and Cluster Computing · Computer Science 2017-02-13 K. Alex Mills , James Smith

Interior point methods for solving linearly constrained convex programming involve a variable projection matrix at each iteration to deal with the linear constraints. This matrix often becomes ill-conditioned near the boundary of the…

Optimization and Control · Mathematics 2024-12-31 Xun Qian , Li-Zhi Liao , Jie Sun

This paper proposes a mechanism to fine-tune convex approximations of probabilistic reachable sets (PRS) of uncertain dynamic systems. We consider the case of unbounded uncertainties, for which it may be impossible to find a bounded…

Robotics · Computer Science 2024-02-06 Pengcheng Wu , Sonia Martinez , Jun Chen

Approximation of non-linear kernels using random feature maps has become a powerful technique for scaling kernel methods to large datasets. We propose $\textit{Tensor Sketch}$, an efficient random feature map for approximating polynomial…

Data Structures and Algorithms · Computer Science 2025-05-20 Ninh Pham , Rasmus Pagh

Given graphs $G$ and $H$, we propose a method to implicitly enumerate topological-minor-embeddings of $H$ in $G$ using decision diagrams. We show a useful application of our method to enumerating subgraphs characterized by forbidden…

Data Structures and Algorithms · Computer Science 2019-11-19 Yu Nakahata , Jun Kawahara , Takashi Horiyama , Shin-ichi Minato

Over the past years, embedding learning on networks has shown tremendous results in link prediction tasks for complex systems, with a wide range of real-life applications. Learning a representation for each node in a knowledge graph allows…

Machine Learning · Computer Science 2026-02-03 Orell Trautmann , Olaf Wolkenhauer , Clémence Réda

Functional lifting methods provide a tool for approximating solutions of difficult non-convex problems by embedding them into a larger space. In this work, we investigate a mathematically rigorous formulation based on embedding into the…

Optimization and Control · Mathematics 2020-07-07 Thomas Vogt , Roland Haase , Danielle Bednarski , Jan Lellmann

In this paper, we study the relations between the numerical structure of the optimal solutions of a convex programming problem defined on the edge set of a simple graph and the stability number (i.e. the maximum size of a subset of pairwise…

Combinatorics · Mathematics 2007-05-23 G. Greco

There are many space subdivision and space partitioning techniques used in many algorithms to speed up computations. They mostly rely on orthogonal space subdivision, resp. using hierarchical data structures, e.g. BSP trees, quadtrees,…

Graphics · Computer Science 2022-08-09 Vaclav Skala

Let $P$ be a set of $n$ points in the plane. We consider a variation of the classical Erd\H{o}s-Szekeres problem, presenting efficient algorithms with $O(n^3)$ running time and $O(n^2)$ space complexity that compute: (1) A subset $S$ of $P$…

Computational Geometry · Computer Science 2024-12-18 Hernán González-Aguilar , David Orden , Pablo Pérez-Lantero , David Rappaport , Carlos Seara , Javier Tejel , Jorge Urrutia

We study dynamic planar graphs with $n$ vertices, subject to edge deletion, edge contraction, edge insertion across a face, and the splitting of a vertex in specified corners. We dynamically maintain a combinatorial embedding of such a…

Data Structures and Algorithms · Computer Science 2022-09-29 Jacob Holm , Ivor van der Hoog , Eva Rotenberg

There has been recent progress in showing that the exponential dependence on treewidth in dynamic programming algorithms for solving NP-hard problems are optimal under the Strong Exponential Time Hypothesis (SETH). We extend this work to…

Data Structures and Algorithms · Computer Science 2015-02-04 Glencora Borradaile , Hung Le

In this paper, we study the mixed-integer nonlinear set given by a separable quadratic constraint on continuous variables, where each continuous variable is controlled by an additional indicator. This set occurs pervasively in optimization…

Optimization and Control · Mathematics 2022-09-07 Andres Gomez , Weijun Xie
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