-
1
-
-
84928636803
-
-
Alexandria, VA: American Statistical Association
-
American Statistical Association Undergraduate Guidelines Workgroup (2014), Curriculum Guidelines for Undergraduate Programs in Statistical Science, Alexandria, VA: American Statistical Association. Available at http://www.amstat.org/education/curriculumguidelines.cfm.
-
(2014)
Curriculum Guidelines for Undergraduate Programs in Statistical Science
-
-
-
2
-
-
0346880128
-
Identification of Causal Effects Using Instrumental Variables
-
J.D.Angrist,, G.W.Imbens,, and D.B.Rubin, (1996), “Identification of Causal Effects Using Instrumental Variables,” Journal of the American Statistical Association, 91, 444–455.
-
(1996)
Journal of the American Statistical Association
, vol.91
, pp. 444-455
-
-
Angrist, J.D.1
Imbens, G.W.2
Rubin, D.B.3
-
3
-
-
84923019894
-
-
ArXiv e-Prints
-
D.Bates,, M.Mächler,, B.Bolker,, and S.Walker, (June 2014), “Fitting Linear Mixed-Effects Models Using lme4,” ArXiv e-Prints.
-
(2014)
Fitting Linear Mixed-Effects Models Using lme4
-
-
Bates, D.1
Mächler, M.2
Bolker, B.3
Walker, S.4
-
4
-
-
0002632234
-
An Introduction to Empirical Bayes Data Analysis
-
G.Casella, (1985), “An Introduction to Empirical Bayes Data Analysis,” The American Statistician, 39, 83–87.
-
(1985)
The American Statistician
, vol.39
, pp. 83-87
-
-
Casella, G.1
-
5
-
-
84952830619
-
Estimating Uncertainty for Massive Data Streams
-
N.Chamandy,, O.Muralidharan,, A.Najmi,, and S.Naidu, (2012), “Estimating Uncertainty for Massive Data Streams,” Internal Technical Report, Google, available at https://static.googleusercontent.com/media/research.google.com/en/us/pubs/archive/43157.pdf.
-
(2012)
Internal Technical Report, Google
-
-
Chamandy, N.1
Muralidharan, O.2
Najmi, A.3
Naidu, S.4
-
7
-
-
84898075653
-
Composite Objective Mirror Descent
-
J.Duchi,, S.Shalev-Shwartz,, Y.Singer,, and A.Tewari, (2010), “Composite Objective Mirror Descent,” in Conference on Learning Theory, Haifa, Israel.
-
(2010)
Conference on Learning Theory
-
-
Duchi, J.1
Shalev-Shwartz, S.2
Singer, Y.3
Tewari, A.4
-
8
-
-
84929731128
-
-
Cambridge, UK: Cambridge University Press
-
B.Efron, (2010), Large-Scale Inference: Empirical Bayes Methods for Estimation, Testing, and Prediction, Cambridge, UK: Cambridge University Press.
-
(2010)
Large-Scale Inference: Empirical Bayes Methods for Estimation, Testing, and Prediction
-
-
Efron, B.1
-
10
-
-
33745697989
-
Creating Non-Parametric Bootstrap Samples Using Poisson Frequencies
-
J.A.Hanley,, and B.MacGibbon, (2006), “Creating Non-Parametric Bootstrap Samples Using Poisson Frequencies,” Computer Methods and Programs in Biomedicine, 83, 57–62.
-
(2006)
Computer Methods and Programs in Biomedicine
, vol.83
, pp. 57-62
-
-
Hanley, J.A.1
MacGibbon, B.2
-
11
-
-
84952779738
-
-
ArXiv e-prints
-
J.Hardin,, R.Hoerl,, N.J.Horton,, and D.Nolan, (October 2014), “Data Science in the Statistics Curricula: Preparing Students to, Think With Data,” ArXiv e-prints.
-
(2014)
Data Science in the Statistics Curricula: Preparing Students to, Think With Data
-
-
Hardin, J.1
Hoerl, R.2
Horton, N.J.3
Nolan, D.4
-
12
-
-
64149115569
-
Sparse Online Learning via Truncated Gradient
-
J.Langford,, L.Li,, and T.Zhang, (2009), “Sparse Online Learning via Truncated Gradient,” Journal of Machine Learning Research, 10, 719–743.
-
(2009)
Journal of Machine Learning Research
, vol.10
, pp. 719-743
-
-
Langford, J.1
Li, L.2
Zhang, T.3
-
13
-
-
27944503134
-
Online Bayesian Bagging
-
H.K.H.Lee,, and M.A.Clyde, (2004), “Online Bayesian Bagging,” The Journal of Machine Learning Research, 5, 143–151.
-
(2004)
The Journal of Machine Learning Research
, vol.5
, pp. 143-151
-
-
Lee, H.K.H.1
Clyde, M.A.2
-
15
-
-
77953338971
-
For Today’s Graduate, Just one Word: Statistics
-
S.Lohr, (2009), “For Today’s Graduate, Just one Word: Statistics,” The New York Times, available at http://www.nytimes.com/2009/08/06/technology/06stats.html?_r=0.
-
(2009)
The New York Times
-
-
Lohr, S.1
-
16
-
-
81055138684
-
-
McKinsey Global Institute
-
J.Manyika,, McKinsey Global C.Institute, Chui, M., B.Brown,, J.Bughin,, R.Dobbs,, C.Roxburgh,, and A.H.Byers, (2011), Big Data: The Next Frontier for Innovation, Competition, and Productivity, McKinsey Global Institute. Available at https://books.google.com/books?id=vN1CYAAACAAJ.
-
(2011)
Big Data: The Next Frontier for Innovation, Competition, and Productivity
-
-
Manyika, J.1
Institute, C.2
Brown, B.3
Bughin, J.4
Dobbs, R.5
Roxburgh, C.6
Byers, A.H.7
-
17
-
-
85022224234
-
-
ACM
-
H.B.McMahan,, G.Holt,, D.Sculley,, M.Young,, D.Ebner,, J.Grady,, L.Nie,, T.Phillips,, E.Davydov,, D.Golovin,, et al. (2013), “Ad Click Prediction: A View From the Trenches,” in Proceedings of the 19th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, ACM, pp. 1222–1230.
-
(2013)
Ad Click Prediction: A View From the Trenches
, pp. 1222-1230
-
-
McMahan, H.B.1
Holt, G.2
Sculley, D.3
Young, M.4
Ebner, D.5
Grady, J.6
Nie, L.7
Phillips, T.8
Davydov, E.9
Golovin, D.10
-
18
-
-
0004188510
-
-
Springer Series in Statistics, New York: Springer
-
D.N.Politis,, J.P.Romano,, and M.Wolf, (1999), Subsampling, Springer Series in Statistics, New York: Springer.
-
(1999)
Subsampling
-
-
Politis, D.N.1
Romano, J.P.2
Wolf, M.3
-
20
-
-
84937926008
-
Feedback Detection for Live Predictors
-
S.Wager,, N.Chamandy,, O.Muralidharan,, and A.Najmi, (2014), “Feedback Detection for Live Predictors,” in Advances in Neural Information Processing Systems, available at http://arxiv.org/abs/1310.2931.
-
(2014)
Advances in Neural Information Processing Systems
-
-
Wager, S.1
Chamandy, N.2
Muralidharan, O.3
Najmi, A.4
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