We give faster approximation algorithms for well-studied variants of Binary Matrix Factorization (BMF), where we are given a binary m × n matrix A and would like to find binary rank-k matrices U, V to minimize the Frobenius norm of U · V - A. In the first setting, U · V ...
We propose a unified framework for Bayesian mean-parameterized nonnegative binary matrix factorization models (NBMF). We analyze three models which correspond to three possible constraints that respect the mean-parameterization without the need for link functions. Furthermore, we derive a novel ...
Binary Matrix Factorization with Applications Chinese Academy of Sciences Chinese Academy of SciencesZhang, ZhongyuanDing, Chris
We introduce binary matrix factorization, a novel model for unsupervised matrix decomposition. The decomposition is learned by fitting a non-parametric Bayesian probabilistic model with binary latent variables to a matrix of dyadic data... D Spiegelman,R Gray 被引量: 61发表: 1991年 Factorizing Three...
matrix into (a distribution defined by) the product , where and are binary feature matrices, and is a real-valued weight matrix. Below, we develop this binary matrix factorization K L J I , = f (A) (B) Figure 1: (A) The graphical model representation of the linear-Gaussian BMF ...
Our formulation does not require a matrix factorization, as previous methods do, but instead looks for projections of the natural parameters from the saturated model. Due to this difference, the number of parameters does not grow with the number of observations and the principal component scores ...
ValueError: Cannot binarize a sparse matrix with threshold < 0 The fit method拟合方法 The fit method exists for the binarizer transformation, but it will not fit anything, it will simply return the object. 存在于二值化处理的拟合方法除了返回对象,没有拟合任何东西。
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Despite its great success, matrix factorization based cross-modality hashing suffers from two problems: 1) there is no engagement between feature learn- ing and binarization; and 2) most existing meth- ods impose the relaxation strategy by discarding the discrete constraints when learning the hash ...
Non-uniqueness of non-negative matrix factorization is a well-known problem. Even after removing trivial degrees of freedom, such as permutation of the components or scaling, the solution of NMF is not generally unique. The uniqueness relates to the form of the decomposition, and the sufficient ...