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For a graph $G$, let $\Pi(G)$ denote the set of all potential maximal cliques of $G$. For each subset $\Pi$ of $\Pi(G)$, let $\tw(G, \Pi)$ denote the smallest $k$ such that there is a tree-decomposition of $G$ of width $k$ whose bags all…

Data Structures and Algorithms · Computer Science 2019-10-25 Hisao Tamaki

In this paper we study quantum algorithms for NP-complete problems whose best classical algorithm is an exponential time application of dynamic programming. We introduce the path in the hypercube problem that models many of these dynamic…

Graphs model real-world circumstances in many applications where they may constantly change to capture the dynamic behavior of the phenomena. Topological persistence which provides a set of birth and death pairs for the topological features…

Computational Geometry · Computer Science 2021-03-15 Tamal K. Dey , Tao Hou

We address highly dynamic distributed systems modeled by time-varying graphs (TVGs). We interest in proof of impossibility results that often use informal arguments about convergence. First, we provide a distance among TVGs to define…

Distributed, Parallel, and Cluster Computing · Computer Science 2014-12-19 Nicolas Braud-Santoni , Swan Dubois , Mohamed-Hamza Kaaouachi , Franck Petit

Recovering the underlying Directed Acyclic Graph (DAG) structures from observational data presents a formidable challenge, partly due to the combinatorial nature of the DAG-constrained optimization problem. Recently, researchers have…

Machine Learning · Computer Science 2025-03-26 Zhen Zhang , Ignavier Ng , Dong Gong , Yuhang Liu , Mingming Gong , Biwei Huang , Kun Zhang , Anton van den Hengel , Javen Qinfeng Shi

Standard simulations of Turing machines suggest a linear relationship between the temporal duration $t$ of a run and the amount of information that must be stored by known simulations to certify, verify, or regenerate the configuration at…

Computational Complexity · Computer Science 2025-12-08 Logan Nye

Decision diagrams (DDs) have emerged as a state-of-the-art method for exact multiobjective integer linear programming. When the DD is too large to fit into memory or the decision-maker prefers a fast approximation to the Pareto frontier,…

Artificial Intelligence · Computer Science 2026-03-20 Rahul Patel , Elias B. Khalil , David Bergman

This paper introduces an online approach for identifying time-varying subspaces defined by linear dynamical systems. The approach of representing linear systems by non-parametric subspace models has received significant interest in the…

Systems and Control · Electrical Eng. & Systems 2025-12-01 András Sasfi , Alberto Padoan , Ivan Markovsky , Florian Dörfler

We show that every directed graph $G$ with $n$ vertices and $m$ edges admits a directed acyclic graph (DAG) with $m^{1+o(1)}$ edges, called a DAG projection, that can either $(1+1/\text{polylog} (n))$-approximate distances between all pairs…

Data Structures and Algorithms · Computer Science 2026-04-07 Bernhard Haeupler , Yonggang Jiang , Thatchaphol Saranurak

Dynamic programming is widely used for exact computations based on tree decompositions of graphs. However, the space complexity is usually exponential in the treewidth. We study the problem of designing efficient dynamic programming…

Data Structures and Algorithms · Computer Science 2014-06-16 Martin Furer , Huiwen Yu

Dynamic programming (DP) is a fundamental tool used across many engineering fields. The main goal of DP is to solve Bellman's optimality equations for a given Markov decision process (MDP). Standard methods like policy iteration exploit the…

Artificial Intelligence · Computer Science 2025-07-30 Sergio Rozada , Samuel Rey , Gonzalo Mateos , Antonio G. Marques

It is shown that $S(G) = O\left(m/\log_2 m + d\right)$ pebbles are sufficient to pebble any DAG $G=(V,E)$, with $m$ edges and maximum in-degree $d$. It was previously known that $S(G) = O\left(d n/\log n\right)$. The result builds on two…

Computational Complexity · Computer Science 2024-10-29 Gianfranco Bilardi , Lorenzo De Stefani

Recently continuous relaxations have been proposed in order to learn Directed Acyclic Graphs (DAGs) from data by backpropagation, instead of using combinatorial optimization. However, a number of techniques for fully discrete…

Machine Learning · Computer Science 2022-10-28 Andrew J. Wren , Pasquale Minervini , Luca Franceschi , Valentina Zantedeschi

Dijkstra's algorithm is the standard method for computing shortest paths on arbitrary graphs. However, it is slow for large graphs, taking at least linear time. It has been long known that for real world road networks, creating a hierarchy…

Data Structures and Algorithms · Computer Science 2023-12-08 Sébastien Collette , John Iacono

Given a set of pairwise disjoint polygonal obstacles in the plane, finding an obstacle-avoiding Euclidean shortest path between two points is a classical problem in computational geometry and has been studied extensively. The previous best…

Computational Geometry · Computer Science 2021-06-01 Haitao Wang

The behavior of the gradient descent (GD) algorithm is analyzed for a deep neural network model with skip-connections. It is proved that in the over-parametrized regime, for a suitable initialization, with high probability GD can find a…

Machine Learning · Computer Science 2019-04-16 Weinan E , Chao Ma , Qingcan Wang , Lei Wu

We revisit the classical Unit Distance Problem posed by Erd\H{o}s in 1946. While the upper bound of $O(n^{4/3})$ established by Spencer, Szemer'edi, and Trotter (1984) is tight for systems of pseudo-circles, it fails to account for the…

Combinatorics · Mathematics 2026-01-28 Lucas Aloisio

Robotic motion-planning problems, such as a UAV flying fast in a partially-known environment or a robot arm moving around cluttered objects, require finding collision-free paths quickly. Typically, this is solved by constructing a graph,…

Robotics · Computer Science 2017-06-29 Sanjiban Choudhury , Shervin Javdani , Siddhartha Srinivasa , Sebastian Scherer

We prove that the true underlying directed acyclic graph (DAG) in Gaussian linear structural equation models is identifiable as the minimum-trace DAG when the error variances are weakly increasing with respect to the true causal ordering.…

Computation · Statistics 2025-08-11 Hyunwoong Chang , Jaehoan Kim

Broadcast domination assigns a nonnegative integer power to every vertex of a graph so that every vertex is within the assigned power of some broadcasting vertex, and the objective is to minimize the sum of the powers. Heggernes and…

Data Structures and Algorithms · Computer Science 2026-05-21 Kleitos Papadopoulos