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arXiv research

A locally-built, LLM-digested index of recent arXiv papers in quant finance, geometry/topology, and statistical ML — keyword search served straight from SQLite on this machine.

168,695 papers · 148 categories

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56112167223 · Jun 202019922001200920172026
48 results for matrix polynomials

The paper defines and classifies Cappell-Shaneson polynomials.

problem Characterizing Cappell-Shaneson polynomials.
method Algebraic conditions on polynomials, reduction modulo primes, and construction of infinite series.
result Complete lists of Cappell-Shaneson polynomials of degrees 4 and 5, and several infinite series of degree 6.

Paper extends Cohen's method to compute Jones polynomial for certain braid subfamilies.

problem Computing Jones polynomial for specific knot families.
method Using weighted adjacency matrices and determinants for certain subfamilies of braid groups.
result Jones polynomial can be computed in polynomial time for certain subfamilies of braid groups.

Graphical notation simplifies complex polynomial constraints in linear models.

problem Complex polynomial constraints in linear structural equation models are impractical.
method Developed a graphical notation to represent these constraints.
result The graphical notation simplifies the representation of many polynomial constraints.

We analyze kernel matrices in polynomial high-dimensional settings and explain double descent in KRR.

problem Understanding the spectrum of kernel matrices in polynomial high-dimensional settings and its implications for KRR risk.
method Generalized decomposition of kernel matrices into low-rank spike matrix, identity, and Gegenbauer matrix.
result The test error in KRR can exhibit double descent behavior, depending on effective regularization and signal-to-noise ratio.

New algorithm optimizes matrix reordering for noisy disordered matrices.

problem Optimizing matrix reordering for noisy disordered matrices in single-cell biology and metagenomics.
method Proposed a polynomial-time adaptive sorting algorithm to improve upon spectral seriation.
result Our algorithm achieves superior performance compared to existing methods in real datasets.

Develops polynomial diffusion models for multi-factor commodity futures dynamics.

problem Modeling futures prices using latent state variables for short and long-term stochastic factors.
method Polynomial diffusion models to incorporate non-linear effects, two filtering methods for estimation.
result Accurate estimation of futures prices despite parameter identification issues in polynomial diffusion models.

The classical Matrix-Tree Theorem allows one to list the spanning trees of a graph by monomials in the expansion of the determinant of a certain matrix. We prove that in the case of three-graphs (that is, hypergraphs whose edges have exactly three vertices) the spanning trees are generated by the Pfaffian of a suitably…

2001-09-17abs ↗pdf ↗

In this paper, a regional knot invariant is constructed. Like the Wirtinger presentation of a knot group, each planar region contributes a generator, and each crossing contributes a relation. The invariant is call a tridle of the link. As in the quandle theory, one can define Alexander quandle and get Alexander polynom…

2017-03-17abs ↗pdf ↗

Researchers compute A-polynomials of manifolds using symplectic properties and cluster algebras.

problem Computing A-polynomials of infinite families of knots and related manifolds is difficult.
method Starting with a triangulation, they use symplectic properties of the Neumann-Zagier matrix to simplify the computation.
result The defining equations of A-polynomials of manifolds obtained by Dehn filling are Ptolemy equations.

We consider a fundamental algorithmic question in spectral graph theory: Compute a spectral sparsifier of random-walk matrix-polynomial Lα(G)=Dr=1dαrD(D1A)rL_α(G)=D-\sum_{r=1}^dα_rD(D^{-1}A)^r where AA is the adjacency matrix of a weighted, undirected graph, DD is the diagonal matrix of weighted degrees, and α=(α1...αd)α=(α_1...α_d) are nonn…

2015-02-12abs ↗pdf ↗

Deep tensor factorization benefits from implicit regularization with polynomial growth.

problem Tensor factorization's implicit regularization effect in deep networks is not well understood.
method Investigated the implicit regularization in deep tensor factorization, showing polynomial growth.
result Implicit regularization in deep tensor factorization grows polynomially with depth, improving estimation accuracy and convergence.

Study reveals an equivalence principle for the spectrum of random inner-product kernel matrices in polynomial scaling.

problem Understanding the spectrum of random kernel matrices in polynomial scaling regimes.
method Investigates random matrices with nonlinear kernel functions applied to inner products of uniformly distributed vectors.
result The spectrum of the random kernel matrix is asymptotically equivalent to a simpler matrix model through free additive convolution.

The Kashaev conjecture is proven for classical signatures and Alexander polynomials of links.

problem Proving the Kashaev conjecture for signatures and Alexander polynomials.
method Relating Kashaev's matrix to Gordon-Litherland's work and Kauffman's model.
result Proven Alexander polynomial and classical signature parts of the conjecture for arbitrary links, and full conjecture for definite knots.

We introduce a new algebraic topological technique to detect non-fibred knots in the three sphere using the twisted Alexander invariants. As an application, we show that for any Seifert matrix of a knot with a nontrivial Alexander polynomial, there exist infinitely many non-fibered knots with the given Seifert matrix. …

2001-09-19abs ↗pdf ↗

Complexity of signed graphs linked to Alexander polynomials and Lehmer's question.

problem Complexity of signed graphs and its relation to Alexander polynomials.
method Definition of graph complexity using Laplacian matrix and Mahler measure, linking to Alexander polynomials and Lehmer's question.
result Complexity growth of signed graphs is related to the growth rate of Alexander polynomials.

This paper studies HOMFLY polynomials of specific and infinite classes of knots.

problem Computing HOMFLY polynomials in general is difficult; this paper examines specific cases.
method Examined two specific knots and a general infinite class of knots.
result Observed apparent patterns in the polynomials of specific knots and conjectured properties of the general class.

This paper presents an algorithm to construct a weighted adjacency matrix of a plane bipartite graph obtained from a pretzel knot diagram. The determinant of this matrix after evaluation is shown to be the Jones polynomial of the pretzel knot by way of perfect matchings (or dimers) of this graph. The weights are Tutte'…

2010-11-16abs ↗pdf ↗

Simplified KR polynomial for bipartite links reduces to tensor products of vector spaces.

problem Complexity reduction of Khovanov-Rozansky polynomial for bipartite links.
method Local reduction of matrix factorizations to planar cycles and simplification to vector spaces.
result KR polynomial for bipartite links simplifies to tensor products of vector spaces.

The paper connects Riemannian Gaussian distributions to random matrix theory and diffusion kernels.

problem Analyzing Riemannian Gaussian distributions on symmetric spaces.
method Analytical computation of marginals using orthogonal and skew orthogonal polynomials, and diffusion kernels.
result Riemannian Gaussian distributions are random matrix types, and their probability density functions can be computed analytically.

The computation of the sparse principal component of a matrix is equivalent to the identification of its principal submatrix with the largest maximum eigenvalue. Finding this optimal submatrix is what renders the problem NP{\mathcal{NP}}-hard. In this work, we prove that, if the matrix is positive semidefinite and its …

2013-12-20abs ↗pdf ↗

Starting from the free field realization of Kac-Moody Lie algebra, we define a generalized Yang-Yang function. Then for the Lie algebra of type AnA_{n}, we derive braiding and fusion matrix by braiding the thimble from the generalized Yang-Yang function. One can construct a knots invariant H(K)H(K) from the braiding and …

2013-12-06abs ↗pdf ↗

We explain an algorithm for finding a boundary link Seifert matrix for a given Alexander polynomial. The algorithm depends on several choices and therefore makes it possible to find non-equivalent Seifert matrices for a given Alexander polynomial.

2003-05-28abs ↗pdf ↗

We present a formula for the trace of any symmetric power of a n×nn\times n matrix (with coefficients in a field) in terms of the ordinary powers of the matrix, an arbitrarily chosen linear function which vanishes on the identity matrix, and n2n-2 polynomial functions defined recursively.

2014-11-03abs ↗pdf ↗

We present two formulas for Chern classes of the tensor product of two vector bundles. In the first formula we consider a matrix containing Chern classes of the first bundle and we take a polynomial of this matrix with Chern classes of the second bundle as coefficients. The determinant of this expression equals the Che…

2019-09-29abs ↗pdf ↗

We develop a method to factorize symmetric sparse Boolean matrices efficiently.

problem Finding a symmetric factorization of a given matrix into a sparse, Boolean matrix.
method Polynomial-time algorithm based on bootstrapping higher-order information and tensor decomposition.
result A matrix with full column rank can be recovered with high probability when the matrix size is sufficiently large.

The ``Links-Gould invariant'' is a two-variable Laurent polynomial invariant of oriented (1,1) tangles, which is derived from the representation of the braid generator associated with the one-parameter family of four dimensional representations with highest weights (0,0|a) of the quantum superalgebra U_q[gl(2|1)]. We u…

1999-09-13abs ↗pdf ↗

A very simple expression is conjectured for arbitrary colored Jones and HOMFLY polynomials of a rich (g+1)(g+1)-parametric family of Pretzel knots and links. The answer for the Jones and HOMFLY polynomials is fully and explicitly expressed through the Racah matrix of U_q(SU_N), and looks related to a modular transformatio…

2014-12-08abs ↗pdf ↗

The paper explores how low-degree polynomials can detect shuffled linear regression models.

problem Detecting multivariate shuffled linear regression models from independent Gaussian random matrices.
method Investigates the effectiveness of low-degree polynomial algorithms for distinguishing the model from independent Gaussian random matrices.
result Establishes a phase transition phenomenon in the performance of low-degree polynomial algorithms for distinguishing the model.

The paper models financial correlation matrices using permutation invariant Gaussian models and predicts market anomalies.

problem Modeling and predicting financial correlation matrices from high-frequency data.
method Constructing permutation invariant Gaussian matrix models with 4 parameters, using graph theory and polynomial functions.
result The permutation invariant Gaussian matrix model predicts the expectation values of cubic and quartic polynomials with strong evidence of fit.

Covariance pooling is a feature pooling method with good classification accuracy. Because covariance features consist of second-order statistics, the scale of the feature elements are varied. Therefore, normalizing covariance features using a matrix square root affects the performance improvement. When pooling methods …

2019-06-05abs ↗pdf ↗

This paper studies how to sketch element-wise functions of low-rank matrices. Formally, given low-rank matrix A = [Aij] and scalar non-linear function f, we aim for finding an approximated low-rank representation of the (possibly high-rank) matrix [f(Aij)]. To this end, we propose an efficient sketching-based algorithm…

2019-05-28abs ↗pdf ↗