A Abstract n algorithm is presented which reduces the prob-m lem of finding the irreducible factors of a bivariate polyno-ial with integer coefficients in polynomial time in the total i degree and the coefficient lengths to factoring a univariate nteger polynomial. Together with A. Lenstra's, H. Lenstra's u and L. Lovasz' polynomial-time factorization algorithm for nivariate integer polynomials...

We introduce a bijection between inequivalent minimal factorizations of the n-cycle (1 2 . . . n) into a product of smaller cycles of given length and trees of a certain structure. A factorization has the type α = (α2, α3, · · · ) if it has αj factors of length j. Inequivalent factorizations are defined up to reordering of commuting factors. A factorization is minimal if no factorizations of a ...

We present a new parallel factorization for band symmetric positive definite (s.p.d) matrices and show some of its applications. Let A be a band s.p.d matrix of order n and half bandwidth m. We show how to factor A as A =DDt Be using approximately 4nm2 jp parallel operations where p =21: is the number of processors. Having this factorization, we improve the time to solve Ax = b by a factor of m...

The perfect 1-factorization conjecture by A. Kotzig [7] asserts the existence of a 1-factorization of a complete graph K2n in which any two 1-factors induce a Hamiltonian cycle. This conjecture is one of the prominent open problems in graph theory. Apart from its theoretical significance it has a number of applications, particularly in designing topologies for wireless communication. Recently, ...

The matrix factorization algorithms such as the matrix factorization technique (MF), singular value decomposition (SVD) and the probability matrix factorization (PMF) and so on, are summarized and compared. Based on the above research work, a kind of improved probability matrix factorization algorithm called MPMF is proposed in this paper. MPMF determines the optimal value of dimension D of bot...

We develop hierarchical Poisson matrix factorization (HPF) for recommendation. HPF models sparse user behavior data, large user/item matrices where each user has provided feedback on only a small subset of items. HPF handles both explicit ratings, such as a number of stars, or implicit ratings, such as views, clicks, or purchases. We develop a variational algorithm for approximate posterior inf...

This paper describes a Multilevel Incomplete QR (MIQR) factorization for solving large sparse least-squares problems. The algorithm builds the factorization by exploiting structural orthogonality in general sparse matrices. At any given step, the algorithm finds an independent set of columns, i.e., a set of columns that have orthogonal patterns. The other columns are then block orthogonalized a...

Tensor factorization arises in many machinelearning applications, such knowledge basemodeling and parameter estimation in latentvariable models. However, numerical meth-ods for tensor factorization have not reachedthe level of maturity of matrix factorizationmethods. In this paper, we propose a newmethod for CP tensor factorization that usesrandom projections to ...

This paper gives an algorithm for solving linear systems, using a randomized version of incomplete LU factorization together with iterative improvement. The factorization uses Gaussian elimination with partial pivoting, and preserves sparsity during factorization by randomized rounding of the entries. The resulting approximate factorization is then applied to estimate the solution. This simple ...

The ring Z consists of the integers of the field Q, and Dedekind takes the theory of unique factorization in Z to be clear and well understood. The problem is that unique factorization can fail when one considers the integers in a finite extension of the rationals, Q(α). Kummer showed that when Q(α) is a cyclotomic extension (i.e. α is a primitive pth root of unity for a prime number p), one ca...