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» Improving spatial locality of programs via data mining
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SDM
2012
SIAM
281views Data Mining» more  SDM 2012»
11 years 10 months ago
Contextual Collaborative Filtering via Hierarchical Matrix Factorization
Matrix factorization (MF) has been demonstrated to be one of the most competitive techniques for collaborative filtering. However, state-of-the-art MFs do not consider contextual...
ErHeng Zhong, Wei Fan, Qiang Yang
RECSYS
2010
ACM
13 years 8 months ago
Incremental collaborative filtering via evolutionary co-clustering
Collaborative filtering is a popular approach for building recommender systems. Current collaborative filtering algorithms are accurate but also computationally expensive, and so ...
Mohammad Khoshneshin, W. Nick Street
PAKDD
2004
ACM
96views Data Mining» more  PAKDD 2004»
14 years 1 months ago
Spectral Energy Minimization for Semi-supervised Learning
The use of unlabeled data to aid classification is important as labeled data is often available in limited quantity. Instead of utilizing training samples directly into semi-super...
Chun Hung Li, Zhi-Li Wu
MICRO
2000
IEEE
80views Hardware» more  MICRO 2000»
14 years 7 days ago
Silent stores for free
Silent store instructions write values that exactly match the values that are already stored at the memory address that is being written. A recent study reveals that significant ...
Kevin M. Lepak, Mikko H. Lipasti
ICDM
2007
IEEE
183views Data Mining» more  ICDM 2007»
14 years 2 months ago
Depth-Based Novelty Detection and Its Application to Taxonomic Research
It is estimated that less than 10 percent of the world’s species have been described, yet species are being lost daily due to human destruction of natural habitats. The job of d...
Yixin Chen, Henry L. Bart Jr., Xin Dang, Hanxiang ...