arXiv research

Study on core consistency preservation in compressed tensors.

Paper simulates LR fuzzy intervals with interval-valued cores.

Linear-Core Surrogates combine fast optimization and statistical efficiency in classification and structured prediction.

This paper establishes an equivalence between transitive double Lie algebroids and core diagrams.

This study examines cores within superclusters, highlighting their transitional nature and dynamical state.

The study shows portfolios based on core-periphery stock structure outperform traditional strategies.

A typical way in which network data is recorded is to measure all the interactions among a specified set of core nodes; this produces a graph containing this core together with a potentially larger set of fringe nodes that have links to the core. Interactions between pairs of nodes in the fringe, however, are not recor…

We consider the space of all quasifuchsian metrics on the product of a surface with the real line. We show that, in a neighborhood of the submanifold consisting of fuchsian metrics, every non-fuchsian metric is completely determined by the bending data of its convex core.

Link prediction benefits from fringe nodes in some datasets but not all.

IllinoisSL is a Java library for learning structured prediction models. It supports structured Support Vector Machines and structured Perceptron. The library consists of a core learning module and several applications, which can be executed from command-lines. Documentation is provided to guide users. In Comparison to …

Dual-Channel Tensor Neural Network (DC-TNN) decomposes tensor data into low-rank and sparse components for better estimation and inference.

We provide initial seedings to the Quick Shift clustering algorithm, which approximate the locally high-density regions of the data. Such seedings act as more stable and expressive cluster-cores than the singleton modes found by Quick Shift. We establish statistical consistency guarantees for this modification. We then…

BIGMACS aligns multiple ocean sediment cores using Bayesian inference and Gaussian process regression.

We extend the notion of a fundamental negatively $\mathbb Z$-graded Lie algebra $\mathfrak{m}_x=\bigoplus_{p\leq -1}\mathfrak{m}_x^p$ associated to any point of a Levi nondegenerate CR manifold to the class of $k$-nondegenerate CR manifolds $(M,\mathcal D,\mathcal J)$ for all $k\geq 2$ and call this invariant the core …

Recovering core nodes in hypergraphs from fringe interactions.

Study finds Aave token network has core-periphery structure, with high decentralization predicting better returns.

New peripheral structure for core groups detects noninvertible knots.

AL$\ell_0$CORE tensor decomposition reduces computational cost for sparse count data.

Interbank markets are often characterised in terms of a core-periphery network structure, with a highly interconnected core of banks holding the market together, and a periphery of banks connected mostly to the core but not internally. This paradigm has recently been challenged for short time scales, where interbank ma…

We introduce the notion of the visual core of a hyperbolic 3-manifold N and explore its basic properties. The visual core can be thought of as a harmonic analysis analogue of the convex core. We investigate circumstances in which the visual core of a cover N' of N embeds under the covering map from N' to N. We apply th…

We prove a conjecture of Menasco and Zhang that if a tangle is completely tubing compressible then it consists of at most two families of parallel strands. This is related to problems of graphs in 3-manifold. A 1-vertex graph $Γ$ in a 3-manifold $M$ with a genus 1 Heegaard splitting is standard if it consists of one or…

New combinatorial structures represent subgroups of surface groups, analogous to Stallings core graphs.

Paper introduces a core-periphery model for identifying informative network structures.

Modified relative universality for unbiasedness and consistency in dimension reduction.

Machine learning aids scientific discoveries by explaining complex data.

Publish a core-set of data to protect against adversarial use.

This work proposes a new method to match distributions across different spaces using cycle-consistent maps.

Estimates covariance matrices for matrix-variate data via core covariance geometry.

Probabilistic programming aids in automatically dating ice cores, reducing manual error and uncertainty.

SySCD improves SCD scalability and speeds up training.

Classifies stability of flat-core $p$-elasticae pinned at boundaries.

Study shows the volume of convex core for once-punctured torus groups is close to a fixed value.

The term "CoRE kernel" stands for correlation-resemblance kernel. In many applications (e.g., vision), the data are often high-dimensional, sparse, and non-binary. We propose two types of (nonlinear) CoRE kernels for non-binary sparse data and demonstrate the effectiveness of the new kernels through a classification ex…

A new tensor model captures complex structures in heterogeneous data.

New algorithm detects cores in graphs with community structure, improving vertex selection for better clustering.

We obtain upper and lower bounds on the difference between the renormalized volume and the volume of the convex core of a convex cocompact hyperbolic 3-manifold which depend on the injectivity radius of the boundary of the universal cover of the convex core and the Euler characteristic of the boundary of the convex cor…

Deep learning predicts nuclear equation of state from rotating core collapse GW signals.

This article was born as a generalisation of the analysis made by Series, where she made the first attempt to plot a deformation space of Kleinian group of more than 1 complex dimension. We use the Top Terms' Relationship proved by the author and Series to determine the asymptotic directions of pleating rays in the Mas…

The study allows for connected sums in manifolds with positive intermediate Ricci curvature.

Study signatures of torus links and their cores using Neumann's equivariant signatures and Hirzebruch's formula.

Proves NP and co-NP status for knot core recognition in solid torus.

Core groups are link invariants defined by arc or region presentations.

We calculated the cross correlations between the half-hourly times series of the ten Dow Jones US economic sectors over the period February 2000 to August 2008, the two-year intervals 2002--2003, 2004--2005, 2008--2009, and also over 11 segments within the present financial crisis, to construct minimal spanning trees (…

Empty core found in max-loss non-centroid clustering.

We show that in any triangulation of a solid torus, there is a pre-core curve that lies in the 2-skeleton and that intersects the interior of each face in at most 10 straight arcs. By definition, a pre-core curve is a simple closed curve that becomes a core curve when a collar is attached to the boundary of the solid t…

CORe uses randomization to explore bandit problems without external noise.

Graph theory provides a language for studying the structure of relations, and it is often used to study interactions over time too. However, it poorly captures the both temporal and structural nature of interactions, that calls for a dedicated formalism. In this paper, we generalize graph concepts in order to cope with…

Convex cores found for group actions on median spaces.