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The most approaches to Knowledge Base Question Answering are based on semantic parsing. In this paper, we address the problem of learning vector representations for complex semantic parses that consist of multiple entities and relations.…

Computation and Language · Computer Science 2018-08-14 Daniil Sorokin , Iryna Gurevych

In this work, we move beyond the traditional complex-valued representations, introducing more expressive hypercomplex representations to model entities and relations for knowledge graph embeddings. More specifically, quaternion embeddings,…

Machine Learning · Computer Science 2019-11-01 Shuai Zhang , Yi Tay , Lina Yao , Qi Liu

Sofic shifts are symbolic dynamical systems defined by the set of bi-infinite sequences on an edge-labeled directed graph, called a presentation. We study the computational complexity of an array of natural decision problems about…

Computational Complexity · Computer Science 2022-09-29 Justin Cai , Rafael Frongillo

Topological drawings are natural representations of graphs in the plane, where vertices are represented by points, and edges by curves connecting the points. Topological drawings of complete graphs and of complete bipartite graphs have been…

Computational Geometry · Computer Science 2017-02-10 Jean Cardinal , Stefan Felsner

Contact representations of graphs have a long history. Most research has focused on problems in 2D, but 3D contact representations have also been investigated, mostly concerning fully-dimensional geometric objects such as spheres or cubes.…

Computational Geometry · Computer Science 2020-04-01 William Evans , Paweł Rzążewski , Noushin Saeedi , Chan-Su Shin , Alexander Wolff

With the rising interest in graph representation learning, a variety of approaches have been proposed to effectively capture a graph's properties. While these approaches have improved performance in graph machine learning tasks compared to…

Machine Learning · Computer Science 2019-10-09 Antonia Gogoglou , C. Bayan Bruss , Keegan E. Hines

In this paper we address the basic geometric question of when a given convex set is the image under a linear map of an affine slice of a given closed convex cone. Such a representation or 'lift' of the convex set is especially useful if the…

Optimization and Control · Mathematics 2013-06-10 João Gouveia , Pablo A. Parrilo , Rekha Thomas

Matching two texts is a fundamental problem in many natural language processing tasks. An effective way is to extract meaningful matching patterns from words, phrases, and sentences to produce the matching score. Inspired by the success of…

Computation and Language · Computer Science 2016-02-23 Liang Pang , Yanyan Lan , Jiafeng Guo , Jun Xu , Shengxian Wan , Xueqi Cheng

Tree representations of (sets of) symmetric binary relations, or equivalently edge-colored undirected graphs, are of central interest, e.g.\ in phylogenomics. In this context symbolic ultrametrics play a crucial role. Symbolic ultrametrics…

Discrete Mathematics · Computer Science 2015-09-18 Marc Hellmuth , Nicolas Wieseke

We develop an algorithmic theory of convex optimization over discrete sets. Using a combination of algebraic and geometric tools we are able to provide polynomial time algorithms for solving broad classes of convex combinatorial…

Optimization and Control · Mathematics 2009-01-24 Shmuel Onn

Let $P$ and $Q$ be two simple polygons in the plane of total complexity $n$, each of which can be decomposed into at most $k$ convex parts. We present an $(1-\varepsilon)$-approximation algorithm, for finding the translation of $Q$, which…

Computational Geometry · Computer Science 2014-06-24 Sariel Har-Peled , Subhro Roy

We show that the core reasons that complex and hypercomplex valued neural networks offer improvements over their real-valued counterparts is the weight sharing mechanism and treating multidimensional data as a single entity. Their algebra…

Neural and Evolutionary Computing · Computer Science 2020-09-10 Chase J Gaudet , Anthony S Maida

A natural generalization of the recognition problem for a geometric graph class is the problem of extending a representation of a subgraph to a representation of the whole graph. A related problem is to find representations for multiple…

Data Structures and Algorithms · Computer Science 2022-09-28 Miriam Münch , Ignaz Rutter , Peter Stumpf

We demonstrate that graph-based models are fully capable of representing higher-order interactions, and have a long history of being used for precisely this purpose. This stands in contrast to a common claim in the recent literature on…

Physics and Society · Physics 2026-02-20 Tiago P. Peixoto , Leto Peel , Thilo Gross , Manlio De Domenico

An emerging solution for explaining Transformer-based models is to use vector-based analysis on how the representations are formed. However, providing a faithful vector-based explanation for a multi-layer model could be challenging in three…

Computation and Language · Computer Science 2023-06-06 Ali Modarressi , Mohsen Fayyaz , Ehsan Aghazadeh , Yadollah Yaghoobzadeh , Mohammad Taher Pilehvar

The literature on word-representable graphs is quite rich, and a number of variations of the original definition have been proposed over the years. We are initiating a systematic study of such variations based on formal languages. In our…

Discrete Mathematics · Computer Science 2024-11-06 Zhidan Feng , Henning Fernau , Pamela Fleischmann , Kevin Mann , Silas Cato Sacher

Many machine learning tasks require finding per-part correspondences between objects. In this work we focus on low-level correspondences - a highly ambiguous matching problem. We propose to use a hierarchical semantic representation of the…

Computer Vision and Pattern Recognition · Computer Science 2017-11-07 Nikolay Savinov , Lubor Ladicky , Marc Pollefeys

A word-representable graph is a simple graph $G$ which can be represented by a word $w$ over the vertices of $G$ such that any two vertices are adjacent in $G$ if and only if they alternate in $w$. It is known that the class of…

Discrete Mathematics · Computer Science 2021-09-09 Khyodeno Mozhui , K. V. Krishna

Tensors are a fundamental data structure for many scientific contexts, such as time series analysis, materials science, and physics, among many others. Improving our ability to produce and handle tensors is essential to efficiently address…

Machine Learning · Statistics 2026-02-12 Wilson G. Gregory , Josué Tonelli-Cueto , Nicholas F. Marshall , Andrew S. Lee , Soledad Villar

Road network is a critical infrastructure powering many applications including transportation, mobility and logistics in real life. To leverage the input of a road network across these different applications, it is necessary to learn the…

Machine Learning · Computer Science 2023-04-18 Liang Zhang , Cheng Long