We develop LIBMF for fully using the computational power of modern multi-core machines to solve several MF problems. The newly added features listed below make LIBMF signi cantly improved in compared with its previous versions. More loss functions are supported for RVMF. The framework is extended to cover BMF, OCMF, and L1 regularization. For di er...
WEBMatrix factorization (MF) plays a key role in many applications such as recommender systems and computer vision, but MF may take long running time for handling large …
WEBIn LIBMF, we parallelize the computation by griding the data matrix. into nr_bins^2 blocks. According to our experiments, this parameter is. not sensitive to both effectiveness and …
WEBJul 12, 2013 · libFM: Factorization Machine Library. Factorization machines (FM) are a generic approach that allows to mimic most factorization models by feature engineering. …
WEBThis way, factorization machines combine the generality of feature engineering with the superiority of factorization models in estimating interactions between categorical …