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Journal ArticleDOI
Hypersharpening by Joint-Criterion Nonnegative Matrix Factorization
TL;DR: Experimental results show that the proposed gradient-based joint-criterion NMF (Grd-JCNMF) methods significantly outperform the well-known coupled NMF sharpening method for most performance figures.
Journal ArticleDOI
A fusion probability matrix factorization framework for link prediction
Zhiqiang Wang,Jiye Liang,Ru Li +2 more
TL;DR: This study develops effective approaches by fusing the adjacent matrix and some key topological metrics in a unified probability matrix factorization framework and presents two fusion models which fuse the two kinds of metrics simultaneously.
Journal ArticleDOI
Nonuniform update for sparse target recovery in fluorescence molecular tomography accelerated by ordered subsets
Dianwen Zhu,Changqing Li +1 more
TL;DR: It is found that the proposed nonuniform updating method outperforms its popular uniform counterpart by obtaining a more localized, less noisy, more accurate image and the computational cost was greatly reduced.
Proceedings ArticleDOI
Practical Data Poisoning Attack against Next-Item Recommendation
TL;DR: Li et al. as discussed by the authors proposed a data poisoning attack against black-box recommendation systems by using reinforcement learning to train an attack agent to generate user behavior samples for data poisoning, without re-training the models within the simulator.
Proceedings ArticleDOI
Situation Aware Multi-task Learning for Traffic Prediction
TL;DR: By incorporating traffic situations, the proposed MTL framework performs consistently better than naively applying MTL per sensor, and outperforms all the best traffic prediction approaches for a given situation by up to 18% and 30% in short and long term predictions, respectively.
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Learning the parts of objects by non-negative matrix factorization
Positive matrix factorization: A non-negative factor model with optimal utilization of error estimates of data values†
Pentti Paatero,Unto Tapper +1 more