@article{inverse,
     jstor_articletype = {research-article},
     title = {On the Inverse of the Sum of Matrices},
     author = {Miller, Kenneth S.},
     journal = {Mathematics Magazine},
     jstor_issuetitle = {},
     volume = {54},
     number = {2},
     jstor_formatteddate = {Mar., 1981},
     pages = {pp. 67-72},
     url = {http://www.jstor.org/stable/2690437},
     ISSN = {0025570X},
     abstract = {},
     language = {English},
     year = {1981},
     publisher = {Mathematical Association of America},
     copyright = {Copyright © 1981 Mathematical Association of America},
}

@article{cook,
     jstor_articletype = {research-article},
     title = {Influential Observations in Linear Regression},
     author = {Cook, R. Dennis},
     journal = {Journal of the American Statistical Association},
     jstor_issuetitle = {},
     volume = {74},
     number = {365},
     jstor_formatteddate = {Mar., 1979},
     pages = {pp. 169-174},
     url = {http://www.jstor.org/stable/2286747},
     ISSN = {01621459},
     language = {English},
     year = {1979},
     publisher = {American Statistical Association},
     copyright = {Copyright © 1979 American Statistical Association},
}

@article{recommendation,
  author    = {Paul D{\"u}tting and
               Monika Rauch Henzinger and
               Ingmar Weber},
  title     = {On the Pricing of Recommendations and Recommending Strategically},
  journal   = {CoRR},
  volume    = {abs/0911.1619},
  year      = {2009},
  ee        = {http://arxiv.org/abs/0911.1619},
  bibsource = {DBLP, http://dblp.uni-trier.de}
}

@inproceedings{shapley,
  author    = {Vishal Misra and
               Stratis Ioannidis and
               Augustin Chaintreau and
               Laurent Massouli{\'e}},
  title     = {Incentivizing peer-assisted services: a fluid shapley value
               approach},
  booktitle = {SIGMETRICS},
  year      = {2010},
  pages     = {215-226},
  ee        = {http://doi.acm.org/10.1145/1811039.1811064},
  crossref  = {DBLP:conf/sigmetrics/2010},
  bibsource = {DBLP, http://dblp.uni-trier.de}
}

@proceedings{DBLP:conf/sigmetrics/2010,
  editor    = {Vishal Misra and
               Paul Barford and
               Mark S. Squillante},
  title     = {SIGMETRICS 2010, Proceedings of the 2010 ACM SIGMETRICS
               International Conference on Measurement and Modeling of
               Computer Systems, New York, New York, USA, 14-18 June 2010},
  booktitle = {SIGMETRICS},
  publisher = {ACM},
  year      = 2010,
  isbn      = {978-1-4503-0038-4},
  bibsource = {DBLP, http://dblp.uni-trier.de}
}

@article {shapleyor,
   author = {Moulin, Hervé and Shenker, Scott},
   affiliation = {Department of Economics, MS 22, Rice University, 6100 Main Street, Houston, TX 77005, USA (e-mail: moulin@rice.edu) US},
   title = {Strategyproof sharing of submodular costs:budget balance versus efficiency},
   journal = {Economic Theory},
   publisher = {Springer Berlin / Heidelberg},
   issn = {0938-2259},
   keyword = {Business and Economics},
   pages = {511-533},
   volume = {18},
   issue = {3},
   url = {http://dx.doi.org/10.1007/PL00004200},
   year = {2001}
}

@inproceedings{subsetselection11,
  author    = {Abhimanyu Das and
               David Kempe},
  title     = {Submodular meets Spectral: Greedy Algorithms for Subset
               Selection, Sparse Approximation and Dictionary Selection},
  booktitle = {ICML},
  year      = {2011},
  pages     = {1057-1064},
  crossref  = {DBLP:conf/icml/2011},
  bibsource = {DBLP, http://dblp.uni-trier.de}
}

@proceedings{DBLP:conf/icml/2011,
  editor    = {Lise Getoor and
               Tobias Scheffer},
  title     = {Proceedings of the 28th International Conference on Machine
               Learning, ICML 2011, Bellevue, Washington, USA, June 28
               - July 2, 2011},
  booktitle = {ICML},
  publisher = {Omnipress},
  year      = {2011},
  bibsource = {DBLP, http://dblp.uni-trier.de}
}

@inproceedings{subsetselection08,
  author    = {Abhimanyu Das and
               David Kempe},
  title     = {Algorithms for subset selection in linear regression},
  booktitle = {STOC},
  year      = 2008,
  pages     = {45-54},
  ee        = {http://doi.acm.org/10.1145/1374376.1374384},
  crossref  = {DBLP:conf/stoc/2008},
  bibsource = {DBLP, http://dblp.uni-trier.de}
}

@proceedings{DBLP:conf/stoc/2008,
  editor    = {Cynthia Dwork},
  title     = {Proceedings of the 40th Annual ACM Symposium on Theory of
               Computing, Victoria, British Columbia, Canada, May 17-20,
               2008},
  booktitle = {STOC},
  publisher = {ACM},
  year      = {2008},
  isbn      = {978-1-60558-047-0},
  bibsource = {DBLP, http://dblp.uni-trier.de}
}

@article{sm,
  title={Adjustment of an inverse matrix corresponding to a change in one element of a given matrix},
  author={Sherman, J. and Morrison, W.J.},
  journal={The Annals of Mathematical Statistics},
  volume={21},
  number={1},
  pages={124--127},
  year={1950},
  publisher={JSTOR}
}

@article{lse,
     jstor_articletype = {research-article},
     title = {Least Squares and Grouping Method Estimators in the Errors in Variables Model},
     author = {Richardson, David H. and Wu, De-Min},
     journal = {Journal of the American Statistical Association},
     jstor_issuetitle = {},
     volume = {65},
     number = {330},
     jstor_formatteddate = {Jun., 1970},
     pages = {pp. 724-748},
     url = {http://www.jstor.org/stable/2284583},
     ISSN = {01621459},
     abstract = {The probability density function of the least squares estimator of the slope coefficient in the errors in variables model is presented. It is shown how the bias and mean-square error of the least squares estimator b depend on the parameters of the model. In particular, for a given sample size, b converges to the true parameter as one of the distribution parameters increased indefinitely. The analysis is supplemented with numerical computations of the relative bias and mean-square error. The distribution function of the grouping method estimator b̄ has the same form as that of b. The biases and mean-square errors of b and b̄ are compared. For the case of zero within-group variance, the use of b̄ always reduces the magnitude of the relative bias and generally reduces the mean-square error. For large values of the within-group variance, use of b̄ may result in an increase in mean-square error.},
     language = {English},
     year = {1970},
     publisher = {American Statistical Association},
     copyright = {Copyright © 1970 American Statistical Association},
    }