-
3
-
-
0242540463
-
Shrinkage estimator generalizations of proximal support vector machines
-
D.K. Agarwal. Shrinkage estimator generalizations of proximal support vector machines. In Proceedings of the 8th Annual ACM SIGKDD Conference, pages 173-182, 2002.
-
(2002)
Proceedings of the 8th Annual ACM SIGKDD Conference
, pp. 173-182
-
-
Agarwal, D.K.1
-
4
-
-
0031334221
-
Selection of relevant features and examples in machine learning
-
A.L. Blum and P. Langley. Selection of relevant features and examples in machine learning. Artificial Intelligence, 97:245-271, 1997.
-
(1997)
Artificial Intelligence
, vol.97
, pp. 245-271
-
-
Blum, A.L.1
Langley, P.2
-
5
-
-
0026453958
-
Training a 3-node neural network is NP-complete
-
A.L. Blum and R.L. Rivest. Training a 3-node neural network is NP-complete. Neural Networks, 5:117-127, 1992.
-
(1992)
Neural Networks
, vol.5
, pp. 117-127
-
-
Blum, A.L.1
Rivest, R.L.2
-
6
-
-
0034507847
-
Combinatorial feature selection problems
-
M. Charikar, V. Guruswami, R. Kumar, S. Rajagopalan, and A. Sahai. Combinatorial feature selection problems. In Proceedings of the 41st Annual IEEE Symposium on Foundations of Computer Science, pages 631-642, 2000.
-
(2000)
Proceedings of the 41st Annual IEEE Symposium on Foundations of Computer Science
, pp. 631-642
-
-
Charikar, M.1
Guruswami, V.2
Kumar, R.3
Rajagopalan, S.4
Sahai, A.5
-
7
-
-
36849041719
-
Algorithms for subset selection in linear regression
-
Manuscript
-
A. Das and D. Kempe. Algorithms for subset selection in linear regression. Manuscript.
-
-
-
Das, A.1
Kempe, D.2
-
12
-
-
0034419669
-
Regularization networks and support vector machines
-
T. Evgeniou, M. Pontil, and T. Poggio. Regularization networks and support vector machines. Advances in Computational Mathematics, 13(1):1-50, 1999.
-
(1999)
Advances in Computational Mathematics
, vol.13
, Issue.1
, pp. 1-50
-
-
Evgeniou, T.1
Pontil, M.2
Poggio, T.3
-
13
-
-
2942731012
-
An extensive empirical study of feature selection metrics for text classification
-
G. Forman. An extensive empirical study of feature selection metrics for text classification. Journal of Machine Learning Research, 3:1289-1305, 2003.
-
(2003)
Journal of Machine Learning Research
, vol.3
, pp. 1289-1305
-
-
Forman, G.1
-
16
-
-
33749382486
-
Text categorization with many redundant features: Using aggressive feature selection to make SVMs competitive with C4.5
-
E. Gabrilovich and S. Markovitch. Text categorization with many redundant features: using aggressive feature selection to make SVMs competitive with C4.5. In Proceedings of the 21th International Conference on Machine Learning, pages 41-48, 2004.
-
(2004)
Proceedings of the 21th International Conference on Machine Learning
, pp. 41-48
-
-
Gabrilovich, E.1
Markovitch, S.2
-
18
-
-
84957069814
-
Text categorization with suport vector machines: Learning with many relevant features
-
T. Joachims. Text categorization with suport vector machines: Learning with many relevant features. In Proceedings of the 10th European Conference on Machine Learning, pages 137-142, 1998.
-
(1998)
Proceedings of the 10th European Conference on Machine Learning
, pp. 137-142
-
-
Joachims, T.1
-
19
-
-
21844475661
-
Dimension reduction in text classification with support vector machines
-
H. Kim, P. Howland, and H. Park. Dimension reduction in text classification with support vector machines. Journal of Machine Learning Research, 6:37-53, 2005.
-
(2005)
Journal of Machine Learning Research
, vol.6
, pp. 37-53
-
-
Kim, H.1
Howland, P.2
Park, H.3
-
20
-
-
0031381525
-
Wrappers for feature subset selection
-
R. Kohavi and G.H. John. Wrappers for feature subset selection. Artificial Intelligence, 97:273-324, 1997.
-
(1997)
Artificial Intelligence
, vol.97
, pp. 273-324
-
-
Kohavi, R.1
John, G.H.2
-
22
-
-
0036161242
-
Text categorization with support vector machines. How to represent texts in input space?
-
E. Leopold and J. Kindermann. Text categorization with support vector machines. How to represent texts in input space? Machine Learning, 46:423-444, 2002.
-
(2002)
Machine Learning
, vol.46
, pp. 423-444
-
-
Leopold, E.1
Kindermann, J.2
-
23
-
-
84876811202
-
RCV1: A new benchmark collection for text categorization research
-
D.D. Lewis, Y. Yang, T.G. Rose, and F. Li. RCV1: A new benchmark collection for text categorization research. Journal of Machine Learning Research, 5:361-397, 2004.
-
(2004)
Journal of Machine Learning Research
, vol.5
, pp. 361-397
-
-
Lewis, D.D.1
Yang, Y.2
Rose, T.G.3
Li, F.4
-
25
-
-
0242705996
-
The mathematics of learning: Dealing with data
-
May
-
T. Poggio and S. Smale. The mathematics of learning: Dealing with data. Notices of the AMS, 50(5):537-544, May 2003.
-
(2003)
Notices of the AMS
, vol.50
, Issue.5
, pp. 537-544
-
-
Poggio, T.1
Smale, S.2
-
27
-
-
9444250658
-
Regularized least-squares classification
-
J.A.K. Suykens, G. Horvath, S. Basu, C. Micchelli, and J. Vandewalle, editors, VIOS Press
-
R. Rifkin, G. Yeo, and T. Poggio. Regularized least-squares classification. In J.A.K. Suykens, G. Horvath, S. Basu, C. Micchelli, and J. Vandewalle, editors, Advances in Learning Theory: Methods, Models and Applications, NATO Science Series III: Computer and Systems Sciences, pages 131-154. VIOS Press, 2003.
-
(2003)
Advances in Learning Theory: Methods, Models and Applications, NATO Science Series III: Computer and Systems Sciences
, pp. 131-154
-
-
Rifkin, R.1
Yeo, G.2
Poggio, T.3
-
28
-
-
36849033560
-
Sampling from large matrices: An approach through geometric functional analysis
-
Manuscript
-
M. Rudelson and R. Vershynin. Sampling from large matrices: an approach through geometric functional analysis. Manuscript.
-
-
-
Rudelson, M.1
Vershynin, R.2
-
30
-
-
84865131152
-
A generalized representer theorem
-
Bernhard Schölkopf, Ralf Herbrich, Alex J. Smola, and Robert C. Williamson. A generalized representer theorem. In Proceedings of the 14th Annual Conference on Computational Learning Theory (COLT 2001) and the 5th European Conference on Computational Learning Theory (EuroCOLT 2001), pages 416-426, 2001.
-
(2001)
Proceedings of the 14th Annual Conference on Computational Learning Theory (COLT 2001) and the 5th European Conference on Computational Learning Theory (EuroCOLT 2001)
, pp. 416-426
-
-
Schölkopf, B.1
Herbrich, R.2
Smola, A.J.3
Williamson, R.C.4
-
31
-
-
0002442796
-
Machine learning in automated text categorization
-
F. Sebastiani. Machine learning in automated text categorization. ACM Computing Surveys, 34(1):1-47, 2002.
-
(2002)
ACM Computing Surveys
, vol.34
, Issue.1
, pp. 1-47
-
-
Sebastiani, F.1
-
33
-
-
0032638628
-
Least squares support vector machine classifiers
-
J.A.K. Suykens and J. Vandewalle. Least squares support vector machine classifiers. Neural Processing Letters, 9(3):293-300, 1999.
-
(1999)
Neural Processing Letters
, vol.9
, Issue.3
, pp. 293-300
-
-
Suykens, J.A.K.1
Vandewalle, J.2
-
42
-
-
0001868572
-
Text categorization based on regularized linear classification methods
-
T. Zhang and F.J. Oles. Text categorization based on regularized linear classification methods. Information Retrieval, 4(1):5-31, 2001.
-
(2001)
Information Retrieval
, vol.4
, Issue.1
, pp. 5-31
-
-
Zhang, T.1
Oles, F.J.2
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