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Every real hyperbolic form in three variables can be realized as the determinant of a linear net of Hermitian matrices containing a positive definite matrix. Such representations are an algebraic certificate for the hyperbolicity of the…

Algebraic Geometry · Mathematics 2015-04-24 Daniel Plaumann , Rainer Sinn , David E. Speyer , Cynthia Vinzant

Linear complementary dual codes (or codes with complementary duals) are codes whose intersections with their dual codes are trivial. We study binary linear complementary dual $[n,k]$ codes with the largest minimum weight among all binary…

Combinatorics · Mathematics 2020-11-20 Masaaki Harada , Ken Saito

We prove that any convex geometry $\mathcal{A}=(U,\mathcal{C})$ on $n$ points and any ideal $\mathcal{I}=(U',\mathcal{C}')$ of $\mathcal{A}$ can be realized as the intersection pattern of an open convex polyhedral cone $K\subseteq {\mathbb…

Combinatorics · Mathematics 2025-07-30 Jérémie Chalopin , Victor Chepoi , Kolja Knauer

Many combinatorial problems can be formulated as a polynomial optimization problem that can be solved by state-of-the-art methods in real algebraic geometry. In this paper we explain many important methods from real algebraic geometry, we…

Combinatorics · Mathematics 2014-11-11 Erik Sjöland

A key technique of machine learning and computer vision is to embed discrete weighted graphs into continuous spaces for further downstream processing. Embedding discrete hierarchical structures in hyperbolic geometry has proven very…

Machine Learning · Computer Science 2023-08-17 Frank Nielsen , Ke Sun

Binary embedding is a nonlinear dimension reduction methodology where high dimensional data are embedded into the Hamming cube while preserving the structure of the original space. Specifically, for an arbitrary $N$ distinct points in…

Data Structures and Algorithms · Computer Science 2019-01-24 Xinyang Yi , Constantine Caramanis , Eric Price

Let $C$ be a non-hyperelliptic algebraic curve. It is known that its canonical image is the intersection of the quadrics that contain it, except when $C$ is trigonal (that is, it has a linear system of degree 3 and dimension 1) or…

Algebraic Geometry · Mathematics 2011-04-14 Josef Schicho , David Sevilla

For monomial special multiserial algebras, which in general are of wild representation type, we construct radical embeddings into algebras of finite representation type. As a consequence, we show that the representation dimension of…

Representation Theory · Mathematics 2017-11-10 Sibylle Schroll

In this paper, we propose a new representation for multiview image sets. Our approach relies on graphs to describe geometry information in a compact and controllable way. The links of the graph connect pixels in different images and…

Multimedia · Computer Science 2013-12-23 Thomas Maugey , Antonio Ortega , Pascal Frossard

A map between operator spaces is called completely coarse if the sequence of its amplifications is equi-coarse. We prove that all completely coarse maps must be $\mathbb R$-linear. On the opposite direction of this result, we introduce a…

Operator Algebras · Mathematics 2020-06-02 Bruno M. Braga , Javier Alejandro Chávez-Domínguez

A graphical realization of a linear code C consists of an assignment of the coordinates of C to the vertices of a graph, along with a specification of linear state spaces and linear ``local constraint'' codes to be associated with the edges…

Discrete Mathematics · Computer Science 2016-11-15 Navin Kashyap

Approaches to signal representation and coding theory have traditionally focused on how to best represent signals using parsimonious representations that incur the lowest possible distortion. Classical examples include linear and non-linear…

Information Theory · Computer Science 2015-12-25 Petros T Boufounos , Shantanu Rane , Hassan Mansour

We introduce a binary embedding framework, called Proximity Preserving Code (PPC), which learns similarity and dissimilarity between data points to create a compact and affinity-preserving binary code. This code can be used to apply fast…

Machine Learning · Computer Science 2020-02-06 Inbal Lav , Shai Avidan , Yoram Singer , Yacov Hel-Or

In the recent years, there has been active research on self-orthogonal embeddings of linear codes since they yielded some optimal self-orthogonal codes. LCD codes have a trivial hull so they are counterparts of self-orthogonal codes. So it…

Information Theory · Computer Science 2026-01-29 Junmin An , Ji-Hoon Hong , Jon-Lark Kim , Haeun Lim

We present a geometric formulation of the Multiple Kernel Learning (MKL) problem. To do so, we reinterpret the problem of learning kernel weights as searching for a kernel that maximizes the minimum (kernel) distance between two convex…

Machine Learning · Computer Science 2014-03-18 John Moeller , Parasaran Raman , Avishek Saha , Suresh Venkatasubramanian

A Lattice is a partially ordered set where both least upper bound and greatest lower bound of any pair of elements are unique and exist within the set. K\"{o}tter and Kschischang proved that codes in the linear lattice can be used for error…

Discrete Mathematics · Computer Science 2021-09-30 Pranab Basu

A Geometric programming (GP) is a type of mathematical problem characterized by objective and constraint functions that have a special form. Many methods have been developed to solve large scale engineering design GP problems. In this paper…

Data Structures and Algorithms · Computer Science 2009-12-10 Dr. A. K. Ojha , K. K. Biswal

Cylindrical algebraic decomposition is a classical construction in real algebraic geometry. Although there are many algorithms to compute a cylindrical algebraic decomposition, their practical performance is still very limited. In this…

Algebraic Geometry · Mathematics 2025-06-05 Rizeng Chen

Let $\mathcal{O}$ be a conic in the classical projective plane $PG(2,q)$, where $q$ is an odd prime power. With respect to $\mathcal{O}$, the lines of $PG(2,q)$ are classified as passant, tangent, and secant lines, and the points of…

Combinatorics · Mathematics 2009-11-12 Peter Sin , Junhua Wu , Qing Xiang

We present a notion of geometry encoding suitable for machine learning-based numerical simulation. In particular, we delineate how this notion of encoding is different than other encoding algorithms commonly used in other disciplines such…

Machine Learning · Computer Science 2021-04-19 Amir Maleki , Jan Heyse , Rishikesh Ranade , Haiyang He , Priya Kasimbeg , Jay Pathak
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