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We study skew-orthogonal polynomials with respect to the weight function $\exp[-2V(x)]$, with $V(x)=\sum_{K=1}^{2d}(u_{K}/{K})x^{K}$, $u_{2d} > 0$, $d > 0$. A finite subsequence of such skew-orthogonal polynomials arising in the study of…

Mathematical Physics · Physics 2015-06-26 Saugata Ghosh

We consider an edge-weighted uniform random graph with a given degree sequence (Repeated Configuration Model) which is a useful approximation for many real-world networks. It has been observed that the vertices which are separated from the…

Probability · Mathematics 2012-09-14 Bartlomiej Blaszczyszyn , Kumar Gaurav

For regular Pareto Fronts (PFs), such as those that are smooth, continuous, and uniformly distributed, using fixed weight vectors is sufficient for multi-objective optimization approaches using decomposition. However, when encountering…

Neural and Evolutionary Computing · Computer Science 2025-11-18 Xiaojing Han , Yuanxin Li

In this paper we provide some exact formulas for projective dimension and the regularity of powers of edge ideals of vertex-weighted rooted forests. These formulas are functions of the weight of the vertices and the number of edges. We also…

Commutative Algebra · Mathematics 2019-04-08 Li Xu , Guangjun Zhu , Hong Wang , Jiaqi Zhang

Understanding the structure of weighted signed networks is essential for analysing social systems in which relationships vary both in sign and strength. Despite significant advances in statistical network analysis, there is still a lack of…

Methodology · Statistics 2025-11-06 Alberto Caimo , Isabella Gollini

Random backpropagation (RBP) is a variant of the backpropagation algorithm for training neural networks, where the transpose of the forward matrices are replaced by fixed random matrices in the calculation of the weight updates. It is…

Machine Learning · Computer Science 2017-12-25 Pierre Baldi , Peter Sadowski , Zhiqin Lu

We show that an algorithmic construction of sequences of recursive trees leads to a direct proof of the convergence of random recursive trees in an associated Doob-Martin compactification; it also gives a representation of the limit in…

Probability · Mathematics 2014-07-01 Rudolf Grübel , Igor Michailow

A single permutation, seen as union of disjoint cycles, represents a regular graph of degree two. Consider $d$ many independent random permutations and superimpose their graph structures. It is a common model of a random regular (multi-)…

Probability · Mathematics 2014-12-30 Shirshendu Ganguly , Soumik Pal

Filters in convolutional networks are typically parameterized in a pixel basis, that does not take prior knowledge about the visual world into account. We investigate the generalized notion of frames designed with image properties in mind,…

Computer Vision and Pattern Recognition · Computer Science 2017-07-20 Jörn-Henrik Jacobsen , Bert de Brabandere , Arnold W. M. Smeulders

We consider a model of random tree growth, where at each time unit a new vertex is added and attached to an already existing vertex chosen at random. The probability with which a vertex with degree $k$ is chosen is proportional to $w(k)$,…

Probability · Mathematics 2007-05-23 Anna Rudas , Balint Toth , Benedek Valko

Residual stress is ubiquitous and indispensable in most biological and artificial materials, where it sustains and optimizes many biological and functional mechanisms. The theory of volume growth, starting from a stress-free initial state,…

Soft Condensed Matter · Physics 2020-09-15 Yangkun Du , Chaofeng Lü , Michel Destrade , Weiqiu Chen

Objects driven through periodically modulated potential-energy landscapes in two dimensions can become locked in to symmetry-selected directions that are independent of the driving force's orientation. We investigate this problem in the…

Soft Condensed Matter · Physics 2007-05-23 Kosta Ladavac , Matthew Pelton , David G. Grier

In this paper we investigate networks whose evolution is governed by the interaction of a random assembly process and an optimization process. In the first process, new nodes are added one at a time and form connections to randomly selected…

Disordered Systems and Neural Networks · Physics 2011-05-16 Markus Brede

This paper tackles the problem of recovering a low-rank signal tensor with possibly correlated components from a random noisy tensor, or so-called spiked tensor model. When the underlying components are orthogonal, they can be recovered…

Machine Learning · Statistics 2023-03-20 Mohamed El Amine Seddik , Mohammed Mahfoud , Merouane Debbah

Gradual semantics with abstract argumentation provide each argument with a score reflecting its acceptability, i.e. how "much" it is attacked by other arguments. Many different gradual semantics have been proposed in the literature, each…

Artificial Intelligence · Computer Science 2022-02-02 Nir Oren , Bruno Yun , Srdjan Vesic , Murilo Baptista

Unitary transformations can allow one to study open quantum systems in situations for which standard, weak-coupling type approximations are not valid. We develop here an extension of the variational (polaron) transformation approach to open…

This paper introduces a new family of multi-parent recombination operators for Genetic Algorithms (GAs), based on normalized Pascal (binomial) coefficients. Unlike classical two-parent crossover operators, Pascal-Weighted Recombination…

Neural and Evolutionary Computing · Computer Science 2026-02-09 Otman A. Basir

Despite the significant recent progress in deep generative models, the underlying structure of their latent spaces is still poorly understood, thereby making the task of performing semantically meaningful latent traversals an open research…

Machine Learning · Computer Science 2023-07-04 Yue Song , T. Anderson Keller , Nicu Sebe , Max Welling

We investigate through computational simulations with a pore network model the formation of patterns caused by erosion-deposition mechanisms. In this model, the geometry of the pore space changes dynamically as a consequence of the coupling…

Computational Physics · Physics 2009-11-13 D. O. Maionchi , A. F. Morais , R. N. Costa Filho , J. S. Andrade , H. J. Herrmann

We study the large-deviation properties of minimum spanning trees for two ensembles of random graphs with $N$ nodes. First, we consider complete graphs. Second, we study Erd\H{o}s-R\'{e}nyi (ER) random graphs with edge probability $p=c/N$…

Disordered Systems and Neural Networks · Physics 2025-12-16 Mahdi Sarikhani , Alexander K. Hartmann