Results 41 to 50 of about 207,171 (287)
Cauchy nonnegative matrix factorization [PDF]
2015 IEEE Workshop on Applications of Signal Processing to Audio and Acoustics (WASPAA), 2015 Nonnegative matrix factorization (NMF) is an effective and popular low-rank model for nonnegative data. It enjoys a rich background, both from an optimization and probabilistic signal processing viewpoint. In this study, we propose a new cost-function for NMF fitting, which is introduced as arising naturally when adopting a Cauchy process model for ...
Liutkus, Antoine +2 more
openaire +2 more sources
Complexity, 2018 We present a novel method, called graph sparse nonnegative matrix factorization, for dimensionality reduction. The affinity graph and sparse constraint are further taken into consideration in nonnegative matrix factorization and it is shown that the ...
Xiangguang Dai +2 more
doaj +1 more source
Non-negative Matrix Factorization Parallel Optimization Algorithm Based on Lp-norm [PDF]
Jisuanji kexueNon-negative matrix factorization algorithm is an important tool for image clustering,data compression and feature extraction.Traditional non-negative matrix factorization algorithms mostly use Euclidean distance to measure reconstruction error,which has
HUANG Lulu, TANG Shuyu, ZHANG Wei, DAI Xiangguang
doaj +1 more source
Improving Recommendation Quality by Merging Collaborative Filtering and Social Relationships [PDF]
, 2011 Matrix Factorization techniques have been successfully applied to raise the quality of suggestions generated\ud by Collaborative Filtering Systems (CFSs).
De Meo, Pasquale +3 more
core +2 more sources
Is Simple Better? Revisiting Non-linear Matrix Factorization for Learning Incomplete Ratings
, 2018 Matrix factorization techniques have been widely used as a method for collaborative filtering for recommender systems. In recent times, different variants of deep learning algorithms have been explored in this setting to improve the task of making a ...
Antulov-Fantulin, Nino +2 more
core +1 more source
LU factorization with panel rank revealing pivoting and its communication avoiding version [PDF]
, 2012 We present the LU decomposition with panel rank revealing pivoting (LU_PRRP), an LU factorization algorithm based on strong rank revealing QR panel factorization. LU_PRRP is more stable than Gaussian elimination with partial pivoting (GEPP).
Demmel, James W. +3 more
core +8 more sources
Kernelized Sparse Bayesian Matrix Factorization
IEEE Transactions on Neural Networks and Learning Systems, 2021 Extracting low-rank and/or sparse structures using matrix factorization techniques has been extensively studied in the machine learning community. Kernelized matrix factorization (KMF) is a powerful tool to incorporate side information into the low-rank approximation model, which has been applied to solve the problems of data mining, recommender ...
Caoyuan Li +5 more
openaire +4 more sources
Personalization Recommendation Algorithm Based on Trust Correlation Degree and Matrix Factorization
IEEE Access, 2019 The rapid development of the Internet of Things (IoT) and e-commerce has brought a lot of convenience to people's lives. IoT applications generate a large number of services and user data.
Weimin Li +6 more
doaj +1 more source
Transductive Nonnegative Matrix Tri-Factorization
IEEE Access, 2020 Nonnegative matrix factorization (NMF) decomposes a nonnegative matrix into the product of two lower-rank nonnegative matrices. Since NMF learns parts-based representation, it has been widely used as a feature learning component in many fields.
Xiao Teng +4 more
doaj +1 more source
Fragmentation, NRQCD and Factorization in Heavy Quarkonium Production
, 2005 We discuss factorization in heavy quarkonium production in high energy collisions using NRQCD. Infrared divergences at NNLO are not matched by conventional NRQCD matrix elements.
Nayak, Gouranga C. +2 more
core +1 more source