Matrix Factorization / Decomposition

7 papers with code • 0 benchmarks • 0 datasets

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Most implemented papers

Joint Matrix-Tensor Factorization for Knowledge Base Inference

dair-iitd/kbi 2 Jun 2017

If not, what characteristics of a dataset determine the performance of MF and TF models?

NuPS: A Parameter Server for Machine Learning with Non-Uniform Parameter Access

alexrenz/NuPS 1 Apr 2021

Parameter servers (PSs) facilitate the implementation of distributed training for large machine learning tasks.

Eigenvalue and Generalized Eigenvalue Problems: Tutorial

bghojogh/Generalized-Eigenvalue-Problem 25 Mar 2019

This paper is a tutorial for eigenvalue and generalized eigenvalue problems.

Fast Rank Reduction for Non-negative Matrices via Mean Field Theory

gkazunii/Legendre-tucker-rank-reduction 9 Jun 2020

We propose an efficient matrix rank reduction method for non-negative matrices, whose time complexity is quadratic in the number of rows or columns of a matrix.

Accurate and fast matrix factorization for low-rank learning

rezagodaz/accurate-partial-svd 21 Apr 2021

In this paper, we tackle two important problems in low-rank learning, which are partial singular value decomposition and numerical rank estimation of huge matrices.

Fast Rank-1 NMF for Missing Data with KL Divergence

gkazunii/A1GM 25 Oct 2021

We propose a fast non-gradient-based method of rank-1 non-negative matrix factorization (NMF) for missing data, called A1GM, that minimizes the KL divergence from an input matrix to the reconstructed rank-1 matrix.