-
1
-
-
0141771188
-
A survey of methods for scaling up inductive algorithms
-
Provost F, Kolluri V. A survey of methods for scaling up inductive algorithms. Data Mining Knowledge Discov 1999; 3: 131-169.
-
(1999)
Data Mining Knowledge Discov
, vol.3
, pp. 131-169
-
-
Provost, F.1
Kolluri, V.2
-
4
-
-
33748544940
-
Network-based marketing: Identifying likely adopters via consumer networks
-
Hill S, Provost F, Volinsky C. Network-based marketing: Identifying likely adopters via consumer networks. Stat Sci 2006; 22: 256-276.
-
(2006)
Stat Sci
, vol.22
, pp. 256-276
-
-
Hill, S.1
Provost, F.2
Volinsky, C.3
-
5
-
-
34447292534
-
Comprehensible credit scoring models using rule extraction from support vector machines
-
Martens D, Baesens B, Van Gestel T, Vanthienen J. Comprehensible credit scoring models using rule extraction from support vector machines. Eur J Oper Res 2007; 183: 1466-1476.
-
(2007)
Eur J Oper Res
, vol.183
, pp. 1466-1476
-
-
Martens, D.1
Baesens, B.2
Van Gestel, T.3
Vanthienen, J.4
-
7
-
-
28444470190
-
RFM, and CLV: Using iso-value curves for customer base analysis
-
Fader PS, Hardie BGS, Ka Lok L. RFM, and CLV: Using iso-value curves for customer base analysis. J Mark Res 2005; 42: 415-430.
-
(2005)
J Mark Res
, vol.42
, pp. 415-430
-
-
Fader, P.S.1
Hardie, B.G.S.2
Ka Lok, L.3
-
8
-
-
70350645569
-
Audience selection for on-line brand advertising: Privacyfriendly social network targeting
-
New York: ACM
-
Provost F, Dalessandro B, Hook R, Zhang X, Murray A. Audience selection for on-line brand advertising: privacyfriendly social network targeting. In: KDD-09: Proceedings of the 15th ACM SIGKDD International Conference on Knowledge Discovery, and Data Mining. New York: ACM, 2009, pp. 707-716.
-
(2009)
KDD-09: Proceedings of the 15th ACM SIGKDD International Conference on Knowledge Discovery, and Data Mining
, pp. 707-716
-
-
Provost, F.1
Dalessandro, B.2
Hook, R.3
Zhang, X.4
Murray, A.5
-
9
-
-
84897110594
-
Machine learning for targeted display advertising: Transfer learning in action
-
Published online; to appear in print
-
Perlich C, Dalessandro B, Raeder T, Stitelman O, Provost F. Machine learning for targeted display advertising: Transfer learning in action. Machine Learning 2013. Published online; to appear in print. DOI 10.1007/.s10994-013-5375-2.
-
(2013)
Machine Learning
-
-
Perlich, C.1
Dalessandro, B.2
Raeder, T.3
Stitelman, O.4
Provost, F.5
-
10
-
-
84898025314
-
Using co-visitation networks for detecting large scale online display advertising exchange fraud
-
Stitelman O, Perlich C, Dalessandro B, Hook R, Raeder T, Provost F. Using co-visitation networks for detecting large scale online display advertising exchange fraud. KDD-13: Proceedings of the 19th ACM SIGKDD International Conference on Knowledge Discovery, and Data Mining. 2013: 1240-1248.
-
(2013)
KDD-13: Proceedings of the 19th ACM SIGKDD International Conference on Knowledge Discovery, and Data Mining
, pp. 1240-1248
-
-
Stitelman, O.1
Perlich, C.2
Dalessandro, B.3
Hook, R.4
Raeder, T.5
Provost, F.6
-
13
-
-
32044451133
-
Distribution-based aggregation for relational learning from identifier attributes
-
Perlich, C, Provost F. Distribution-based aggregation for relational learning from identifier attributes. Machine Learning 2006; 62(1/2): 65-105.
-
(2006)
Machine Learning
, vol.62
, Issue.1-2
, pp. 65-105
-
-
Perlich, C.1
Provost, F.2
-
14
-
-
71149087699
-
Feature hashing for large scale multitask learning
-
Weinberger K, Dasgupta A, Langford J, Smola A, Attenberg J. Feature hashing for large scale multitask learning. In: Proceedings of the 26th Annual International Conference on Machine Learning, 2009, pp. 1113-1120.
-
(2009)
Proceedings of the 26th Annual International Conference on Machine Learning
, pp. 1113-1120
-
-
Weinberger, K.1
Dasgupta, A.2
Langford, J.3
Smola, A.4
Attenberg, J.5
-
15
-
-
1242268938
-
Tree induction vs. Logistic regression: A learning-curve analysis
-
Perlich C, Provost F, Simonoff JS. Tree induction vs. logistic regression: A learning-curve analysis. JMLR 2003; 4: 211-255.
-
(2003)
JMLR
, vol.4
, pp. 211-255
-
-
Perlich, C.1
Provost, F.2
Simonoff, J.S.3
-
16
-
-
0030127467
-
Scaling up inductive learning with massive parallelism
-
Provost F, Aronis J. Scaling up inductive learning with massive parallelism. Machine Learning 1996; 23: 33-46.
-
(1996)
Machine Learning
, vol.23
, pp. 33-46
-
-
Provost, F.1
Aronis, J.2
-
17
-
-
84991693451
-
Machine learning, and algorithms: Agile development
-
Langford J, Ortega R. Machine learning, and algorithms: Agile development. Commun ACM 2012; 55: 10-11.
-
(2012)
Commun ACM
, vol.55
, pp. 10-11
-
-
Langford, J.1
Ortega, R.2
-
19
-
-
84991746870
-
Bring the noise: Embracing randomness is the key to scaling up machine learning algorithms
-
Dalessandro B. Bring the noise: Embracing randomness is the key to scaling up machine learning algorithms. Big Data J 2013; 1: 105-109.
-
(2013)
Big Data J
, vol.1
, pp. 105-109
-
-
Dalessandro, B.1
-
20
-
-
59549087165
-
On discriminative vs. Generative classifiers: A comparison of logistic regression, and Naive Bayes
-
Ng A, Jordan M. On discriminative vs. generative classifiers: A comparison of logistic regression, and Naive Bayes. Adv Neural Inf Process Syst 2002; 14: 841.
-
(2002)
Adv Neural Inf Process Syst
, vol.14
, pp. 841
-
-
Ng, A.1
Jordan, M.2
-
21
-
-
84887588389
-
Data Science for Business-What you need to know about data mining, and data-Analytic thinking
-
Provost F, Fawcett T. Data Science for Business-What you need to know about data mining, and data-Analytic thinking. O'Reilly Media, 2013.
-
(2013)
O'Reilly Media
-
-
Provost, F.1
Fawcett, T.2
-
22
-
-
0031381525
-
Wrappers for feature subset selection
-
Kohavi R, John GH. Wrappers for feature subset selection. Artif Intell 1997; 97: 273-324.
-
(1997)
Artif Intell
, vol.97
, pp. 273-324
-
-
Kohavi, R.1
John, G.H.2
-
23
-
-
44949274046
-
The theory of planned behavior
-
Ajzen I. The theory of planned behavior. Theor Cogn Self Regul 1991; 50: 179-211.
-
(1991)
Theor Cogn Self Regul
, vol.50
, pp. 179-211
-
-
Ajzen, I.1
-
24
-
-
0016220640
-
Attitudes towards objects as predictors of single, and multiple behavioral criteria
-
Fishbein M, Ajzen I. Attitudes towards objects as predictors of single, and multiple behavioral criteria. Psychol Rev 1974; 81: 59-74.
-
(1974)
Psychol Rev
, vol.81
, pp. 59-74
-
-
Fishbein, M.1
Ajzen, I.2
-
25
-
-
33645657113
-
Improving recommendation lists through topic diversification
-
New York ACM
-
Ziegler C-N, McNee S, Konstan JA, Lausen G. Improving recommendation lists through topic diversification. In: Proceedings of the 14th International Conference on World Wide Web. New York: ACM, 2005, pp. 22-32.
-
(2005)
Proceedings of the 14th International Conference on World Wide Web
, pp. 22-32
-
-
Ziegler, C.-N.1
McNee, S.2
Konstan, J.A.3
Lausen, G.4
-
28
-
-
71149108237
-
Identifying suspicious URLs: An application of large-scale online learning
-
Ma J, Saul LK, Savage S, Voelker GM. Identifying suspicious URLs: An application of large-scale online learning. In: ICML-09 Proceedings of the 26th Annual International Conference on Machine Learning, 2009, pp. 681-688.
-
(2009)
ICML-09 Proceedings of the 26th Annual International Conference on Machine Learning
, pp. 681-688
-
-
Ma, J.1
Saul, L.K.2
Savage, S.3
Voelker, G.M.4
-
32
-
-
84991572246
-
-
May 8 2013). Management Science, Forthcoming. Available at SSRN
-
Tambe, P. Big Data Investment, Skills, and Firm Value (May 8, 2013). Management Science, Forthcoming. Available at SSRN: http://ssrn.com/abstract=2294077 or http://.dx.doi.org/10.2139/ssrn.2294077
-
Big Data Investment Skills Firm Value
-
-
Tambe, P.1
-
33
-
-
84991650406
-
-
Fast Company, September 16, 2013. Last accessed on October 1, 2013
-
Gray T. 2013. Dstillery is Picasso in the dark art of digital advertising. Fast Company, September 16, 2013. www.fastcompany.com/3017495/dstillery-is-picasso-in-Thedark-Art-of-digital-Advertising. (Last accessed on October 1, 2013
-
(2013)
Dstillery Is Picasso in the Dark Art of Digital Advertising
-
-
Gray, T.1
-
34
-
-
33745156863
-
Some theory for Fisher's linear discriminant function, naive Bayes, and some alternatives when there are many more variables than observations
-
Bickel PJ, Levina E. Some theory for Fisher's linear discriminant function, naive Bayes, and some alternatives when there are many more variables than observations. Bernoulli 2004; 10: 989-1010.
-
(2004)
Bernoulli
, vol.10
, pp. 989-1010
-
-
Bickel, P.J.1
Levina, E.2
|