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We consider a serious, previously-unexplored challenge facing almost all approaches to scaling up entity resolution (ER) to multiple data sources: the prohibitive cost of labeling training data for supervised learning of similarity scores for each pair of sources.
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Nonparametric regression and classification with joint sparsity constraints
H. Liu, J. Lafferty, and L. Wasserman · 2008
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S. A. van de Geer · 2008
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Simultaneous analysis of Lasso and Dantzig selector
P. J. Bickel, Y. Ritov, and A. Tsybakov · 2009
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Z. Chen, D. V. Kalashnikov, and S. Mehrotra · 2009
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S. Negahban, P. Ravikumar, M. J. Wainwright, and B. Yu · 2009
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Y. Nesterov · 2007
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Frameworks for entity matching: A comparison
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Evaluation of entity resolution approaches on real-world match problems
H. Köpcke, A. Thor, and E. Rahm · 2010
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Rank-sparsity incoherence for matrix decomposition
V. Chandrasekaran, S. Sanghavi, P. A. Parrilo, and A. S. Willsky · 2011
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