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We want to construct a homological link invariant whose Euler characteristic is MOY polynomial as Khovanov and Rozansky constructed a categorification of HOMFLY polynomial. The present paper gives the first step to construct a…

Quantum Algebra · Mathematics 2008-07-01 Yasuyoshi Yonezawa

In this work, we study a class of random matrices which interpolate between the Wigner matrix model and various types of patterned random matrices such as random Toeplitz, Hankel, and circulant matrices. The interpolation mechanism is…

Probability · Mathematics 2024-05-14 Frederick Rajasekaran

For a sufficiently nice 2 dimensional shape, we define its approximating matrix (or patterned matrix) as a random matrix with iid entries arranged according to a given pattern. For large approximating matrices, we observe that the…

Probability · Mathematics 2022-01-04 Tapesh Yadav

Automated per-instance algorithm selection and configuration have shown promising performances for a number of classic optimization problems, including satisfiability, AI planning, and TSP. The techniques often rely on a set of features…

Neural and Evolutionary Computing · Computer Science 2020-10-01 Tome Eftimov , Gorjan Popovski , Quentin Renau , Peter Korosec , Carola Doerr

We investigate compressibility of the dimension of positive semidefinite matrices while approximately preserving their pairwise inner products. This can either be regarded as compression of positive semidefinite factorizations of…

Quantum Physics · Physics 2016-05-06 Cyril J. Stark , Aram W. Harrow

In this article we are interested for the numerical study of nonlinear eigenvalue problems. We begin with a review of theoretical results obtained by functional analysis methods, especially for the Schrodinger pencils. Some recall are given…

Numerical Analysis · Mathematics 2016-08-24 Fatima Aboud , Francois Jauberteau , Guy Moebs , Didier Robert

Existing nonnegative matrix factorization methods focus on learning global structure of the data to construct basis and coefficient matrices, which ignores the local structure that commonly exists among data. In this paper, we propose a new…

Machine Learning · Computer Science 2019-07-10 Chong Peng , Zhao Kang , Chenglizhao Chen , Qiang Cheng

We propose a deep factorization model for typographic analysis that disentangles content from style. Specifically, a variational inference procedure factors each training glyph into the combination of a character-specific content embedding…

Machine Learning · Computer Science 2020-05-19 Nikita Srivatsan , Jonathan T. Barron , Dan Klein , Taylor Berg-Kirkpatrick

We study tensor network varieties associated with the triangular graph, with a focus on the case where one of the physical dimensions is 2. This allows us to interpret the tensors as pencils of matrices. We provide a complete…

Algebraic Geometry · Mathematics 2026-02-18 Alessandra Bernardi , Fulvio Gesmundo

A very elementary model of a single positive hermitian random matrix coupled to an external matrix is defined and studied. Expanding the exact effective action around its classical solution leads to the ``quantum Penner action'', from which…

High Energy Physics - Theory · Physics 2008-02-03 Camillo Imbimbo , Sunil Mukhi

Matrix factorization is a key tool in data analysis; its applications include recommender systems, correlation analysis, signal processing, among others. Binary matrices are a particular case which has received significant attention for…

Machine Learning · Statistics 2019-01-30 Ignacio Ramirez

In this work, we propose an approach for assessing sensitivity to unobserved confounding in studies with multiple outcomes. We demonstrate how prior knowledge unique to the multi-outcome setting can be leveraged to strengthen causal…

Methodology · Statistics 2023-01-26 Jiajing Zheng , Jiaxi Wu , Alexander D'Amour , Alexander Franks

Mechanistic interpretability aims to understand how neural networks generalize beyond their training data by reverse-engineering their internal structures. We introduce patterning as the dual problem: given a desired form of generalization,…

Machine Learning · Computer Science 2026-01-21 George Wang , Daniel Murfet

Factor models are widely used for dimension reduction in the analysis of multivariate data. This is achieved through decomposition of a p x p covariance matrix into the sum of two components. Through a latent factor representation, they can…

Methodology · Statistics 2024-07-01 Sarah Elizabeth Heaps , Ian Hyla Jermyn

We investigate tensor products of matrix factorisations. This is most naturally done by formulating matrix factorisations in terms of bimodules instead of modules. If the underlying ring is C[x_1,...,x_N] we show that bimodule matrix…

Mathematical Physics · Physics 2014-11-20 Nils Carqueville , Ingo Runkel

We investigate the analytic structure of scattering amplitudes in theories in which Lorentz invariance is spontaneously broken. We do so by computing and studying the S-matrix for a simple example: a superfluid described by a complex scalar…

High Energy Physics - Theory · Physics 2023-12-15 Lam Hui , Ioanna Kourkoulou , Alberto Nicolis , Alessandro Podo , Shengjia Zhou

We study processes with unstable particles in intermediate time-like states. It is shown that the amplitudes squared of such processes factor exactly in the framework of the model of unstable particles with continuous masses. Decay widths…

High Energy Physics - Phenomenology · Physics 2013-03-22 V. Kuksa , N. Volchanskiy

Pencils of Hankel matrices whose elements have a joint Gaussian distribution with nonzero mean and not identical covariance are considered. An approximation to the distribution of the squared modulus of their determinant is computed which…

Statistics Theory · Mathematics 2012-09-28 Piero Barone

We describe here a framework for a certain class of multiscale likelihood factorizations wherein, in analogy to a wavelet decomposition of an L^2 function, a given likelihood function has an alternative representation as a product of…

Statistics Theory · Mathematics 2007-06-13 Eric D. Kolaczyk , Robert D. Nowak

In Parts I and II of this series of papers, three new methods for the computation of eigenvalues of singular pencils were developed: rank-completing perturbations, rank-projections, and augmentation. It was observed that a straightforward…

Numerical Analysis · Mathematics 2024-06-12 Michiel E. Hochstenbach , Christian Mehl , Bor Plestenjak
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