Abstract: Sparse nonnegative matrix factorization (SNMF) aims to factorize a data matrix into two optimized nonnegative sparse factor matrices, which could benefit many tasks, such as document-word co ...

pip install torch==1.7.1+cu101 torchvision==0.8.2+cu101 -f https://download.pytorch.org/whl/torch_stable.html from tddl.factorizations import factorize_network ...

PRIMUS is a holistic clustering approach that identifies phenotypic cell groups from the scRNA-seq data while accounting for date source (e.g. patient, sample, dataset) -specific components as well as ...

“Q-Day” is the term some experts use to describe when large-scale quantum computers are able to factorize the large prime numbers that underlie our public encryption systems, such as the ones that are ...

Abstract: Recommender systems are an important kind of learning systems, which can be achieved by latent-factor (LF)-based collaborative filtering (CF) with high efficiency and scalability. LF-based ...