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- The "DGX" Distribution for Mining Massive, Skewed Data
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- Finding structure with randomness: Stochastic algorithms for constructing approximate matrix decompositions N. Halko, P. Martinsson, and J. Tropp
- GraphLab: A New Parallel Framework for Machine Learning
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- Hadoop: The Definitive Guide
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- Introduction to Data Mining
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- Large Linear Classification When Data Cannot Fit In Memory
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- Less is More: Compact Matrix Decomposition for Large Sparse Graphs
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- LSQR: An Algorithm for Sparse Linear Equations and Sparse Least Squares
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- LIBLINEAR: A Library for Large Linear Classification
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- Map-Reduce for machine learning on multicore
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- Mining Frequent Patterns without Candidate Generation
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- Pegasos: Primal Estimated sub-GrAdient SOlver for SVM
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- Tackling the Poor Assumptions of Naive Bayes Text Classifiers
J. D. M. Rennie, L. Shih, J. Teevan, and D. R. Karger
- Top 10 algorithms in data mining
X. Wu, V. Kumar, J. Quinlan, J. Ghosh, Q. Yang, H. Motoda, g. McLachlan, A. Ng, B. Liu, P. Yu, Z. Zhou, M. Steinbach, D. Hand, and D. Steinberg
- Toward the Next Generation of Recommender Systems: A Survey of the State-of-the-Art and Possible Extensions
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- A Tutorial on Spectral Clustering
U. Luxburg
- Using collaborative filtering to weave an information tapestry
D. Goldber, D. Nichols, B. Oki, and D. Terry
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