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The aim in many sciences is to understand the mechanisms that underlie the observed distribution of variables, starting from a set of initial hypotheses. Causal discovery allows us to infer mechanisms as sets of cause and effect…

Machine Learning · Computer Science 2025-03-05 Ashka Shah , Adela DePavia , Nathaniel Hudson , Ian Foster , Rick Stevens

In the constraint programming framework, state-of-the-art static and dynamic decomposition techniques are hard to apply to problems with complete initial constraint graphs. For such problems, we propose a hybrid approach of these techniques…

Computational Complexity · Computer Science 2008-12-18 Stephane Zampelli , Martin Mann , Yves Deville , Rolf Backofen

Benchmarking anomaly detection approaches for multivariate time series is a challenging task due to a lack of high-quality datasets. Current publicly available datasets are too small, not diverse and feature trivial anomalies, which hinders…

Machine Learning · Computer Science 2025-11-13 Lucas Correia , Jan-Christoph Goos , Thomas Bäck , Anna V. Kononova

In this paper we revisit the classical Edge Disjoint Paths (EDP) problem, where one is given an undirected graph G and a set of terminal pairs P and asks whether G contains a set of pairwise edge-disjoint paths connecting every terminal…

Data Structures and Algorithms · Computer Science 2017-11-07 Robert Ganian , Sebastian Ordyniak , M. S. Ramanujan

Today's scene graph generation (SGG) task is still far from practical, mainly due to the severe training bias, e.g., collapsing diverse "human walk on / sit on / lay on beach" into "human on beach". Given such SGG, the down-stream tasks…

Computer Vision and Pattern Recognition · Computer Science 2025-10-28 Kaihua Tang , Yulei Niu , Jianqiang Huang , Jiaxin Shi , Hanwang Zhang

The dramatic success of deep neural networks across multiple application areas often relies on experts painstakingly designing a network architecture specific to each task. To simplify this process and make it more accessible, an emerging…

Machine Learning · Computer Science 2018-01-17 Kamil Bennani-Smires , Claudiu Musat , Andreea Hossmann , Michael Baeriswyl

Deep learning-based graph generation approaches have remarkable capacities for graph data modeling, allowing them to solve a wide range of real-world problems. Making these methods able to consider different conditions during the generation…

Machine Learning · Computer Science 2023-01-11 Faezeh Faez , Negin Hashemi Dijujin , Mahdieh Soleymani Baghshah , Hamid R. Rabiee

Paths $P_1,\ldots, P_k$ in a graph $G=(V,E)$ are mutually induced if any two distinct $P_i$ and $P_j$ have neither common vertices nor adjacent vertices. The Induced Disjoint Paths problem is to decide if a graph $G$ with $k$ pairs of…

Combinatorics · Mathematics 2022-07-19 Barnaby Martin , Daniël Paulusma , Siani Smith , Erik Jan van Leeuwen

Beam search is a go-to strategy for decoding neural sequence models. The algorithm can naturally be viewed as a subset optimization problem, albeit one where the corresponding set function does not reflect interactions between candidates.…

Computation and Language · Computer Science 2023-06-26 Clara Meister , Martina Forster , Ryan Cotterell

A geographic network is a graph whose vertices are restricted to lie in a prescribed region in the plane. In this paper we begin to study the following fundamental problem for geographic networks: can a given geographic network be drawn…

Computational Geometry · Computer Science 2023-06-22 Rodrigo I. Silveira , Bettina Speckmann , Kevin Verbeek

We consider the parameterized complexity of the problem of tracking shortest s-t paths in graphs, motivated by applications in security and wireless networks. Given an undirected and unweighted graph with a source s and a destination t,…

Data Structures and Algorithms · Computer Science 2020-08-19 Aritra Banik , Pratibha Choudhary , Venkatesh Raman , Saket Saurabh

Identifying causal relations among multi-variate time series is one of the most important elements towards understanding the complex mechanisms underlying the dynamic system. It provides critical tools for forecasting, simulations and…

Machine Learning · Computer Science 2023-02-22 Yang Sun , Yifan Xie

Transferrable neural architecture search can be viewed as a binary optimization problem where a single optimal path should be selected among candidate paths in each edge within the repeated cell block of the directed a cyclic graph form.…

Computer Vision and Pattern Recognition · Computer Science 2019-12-05 Hyeong Gwon Hong , Pyunghwan Ahn , Junmo Kim

Map matching is a common preprocessing step for analysing vehicle trajectories. In the theory community, the most popular approach for map matching is to compute a path on the road network that is the most spatially similar to the…

Computational Geometry · Computer Science 2024-01-26 Joachim Gudmundsson , Martin P. Seybold , Sampson Wong

Let $P$ be a set of $n \geq 5$ points in convex position in the plane. The path graph $G(P)$ of $P$ is an abstract graph whose vertices are non-crossing spanning paths of $P$, such that two paths are adjacent if one can be obtained from the…

Combinatorics · Mathematics 2018-01-03 Chaya Keller , Yael Stein

Path planning is an active area of research essential for many applications in robotics. Popular techniques include graph-based searches and sampling-based planners. These approaches are powerful but have limitations. This paper continues…

Robotics · Computer Science 2020-12-10 Marlin P. Strub , Jonathan D. Gammell

Differential Neural Architecture Search (NAS) methods represent the network architecture as a repetitive proxy directed acyclic graph (DAG) and optimize the network weights and architecture weights alternatively in a differential manner.…

Computer Vision and Pattern Recognition · Computer Science 2020-12-01 Benteng Ma , Jing Zhang , Yong Xia , Dacheng Tao

We consider the problem of finding edge-disjoint paths between given pairs of vertices in a sufficiently strong $d$-regular expander graph $G$ with $n$ vertices. In particular, we describe a deterministic, polynomial time algorithm which…

Data Structures and Algorithms · Computer Science 2023-10-23 Nemanja Draganić , Rajko Nenadov

Performing analytical tasks over graph data has become increasingly interesting due to the ubiquity and large availability of relational information. However, unlike images or sentences, there is no notion of sequence in networks. Nodes…

Neural and Evolutionary Computing · Computer Science 2020-10-28 Matheus Nunes , Gisele L. Pappa

Constructing a spanning tree of a graph is one of the most basic tasks in graph theory. We consider this problem in the setting of local algorithms: one wants to quickly determine whether a given edge $e$ is in a specific spanning tree,…

Data Structures and Algorithms · Computer Science 2021-04-28 Reut Levi , Dana Ron , Ronitt Rubinfeld
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