2018年12月17日 · We propose a unified framework for Bayesian mean-parameterized nonnegative binary matrix factorization models (NBMF). We analyze three models which …

2018年12月17日 · We propose a unified framework for Bayesian mean-parameterized nonnegative binary matrix factorization models (NBMF). We analyze three models which …

2020年4月30日 · We introduce negative binomial matrix factorization (NBMF), a matrix factorization technique specially designed for analyzing over-dispersed count data. It can be …

Code for our paper "Bayesian Mean-parameterized Nonnegative Binary Matrix Factorization" - NBMF/README.md at master · alumbreras/NBMF

我们引入负二项式矩阵分解（NBMF），这是一种专为分析过度分散计数数据而设计的矩阵分解技术。 它可以被视为泊松分解 (PF) 的扩展，受到模拟暴露的乘法项的扰动。

main_script.py trains the models (NBMF-EM, NBMF-MM, and logPCA) while performing validation (minimize perplexity on the validation set), to tune the hyperparameters. It also predict the test …

2024年11月18日 · nbmf属于协同过滤中的一种，尤其是模型基础协同过滤方法，它可以处理用户或物品的缺失数据，为每个用户和物品生成隐因子表示。 4. Python编程语言： Python是一种 …

Nonnegative/binary matrix factorization (NBMF) was originally introduced as a generative model, and we propose a multiclass classification model as an application. We extract the...

2018年1月5日 · We introduce negative binomial matrix factorization (NBMF), a matrix factorization technique specially designed for analyzing over-dispersed count data. It can be viewed as an …

2020年7月2日 · Using nonnegative/binary matrix factorization (NBMF), a matrix can be decomposed into a nonnegative matrix and a binary matrix. Our analysis of facial images, …