-
1
-
-
0000874557
-
Theoretical foundations of the potential function method in pattern recognition learning
-
M. Aizerman, E. Braverman, and L. Rozonoer. Theoretical foundations of the potential function method in pattern recognition learning. Automation and Remote Control, 25:821 - 837, 1964.
-
(1964)
Automation and Remote Control
, vol.25
, pp. 821-837
-
-
Aizerman, M.1
Braverman, E.2
Rozonoer, L.3
-
2
-
-
0034598746
-
Distinct types of diffues large b-cell lymphoma identified by gene expression profiling
-
A.A. Alizadeh. Distinct types of diffues large b-cell lymphoma identified by gene expression profiling. Nature, 403:503-511, 2000.
-
(2000)
Nature
, vol.403
, pp. 503-511
-
-
Alizadeh, A.A.1
-
3
-
-
0033536012
-
Broad patterns of gene expression revealed by clustering analysis of tumor and normal colon cancer tissues probed by oligonucleotide arrays
-
U. Alon, N. Barkai, D. Notterman, K. Gish, S. Ybarra, D. Mack, and A. Levine. Broad patterns of gene expression revealed by clustering analysis of tumor and normal colon cancer tissues probed by oligonucleotide arrays. Cell Biology, 96:6745-6750, 1999.
-
(1999)
Cell Biology
, vol.96
, pp. 6745-6750
-
-
Alon, U.1
Barkai, N.2
Notterman, D.3
Gish, K.4
Ybarra, S.5
Mack, D.6
Levine, A.7
-
4
-
-
0004493166
-
On the approximability of minimizing non zero variables or unsatisfied relations in linear systems
-
E. Amaldi and V. Kann. On the approximability of minimizing non zero variables or unsatisfied relations in linear systems. Theoretical Computer Science, 209:237-260, 1998.
-
(1998)
Theoretical Computer Science
, vol.209
, pp. 237-260
-
-
Amaldi, E.1
Kann, V.2
-
5
-
-
0026860799
-
Robust linear programming discrimination of two linearly inseparable sets
-
K. P. Bennett and O. L. Mangasarian. Robust linear programming discrimination of two linearly inseparable sets. Optimization Methods and Software, 1:23-34, 1992.
-
(1992)
Optimization Methods and Software
, vol.1
, pp. 23-34
-
-
Bennett, K.P.1
Mangasarian, O.L.2
-
6
-
-
0031334221
-
Selection of relevant features and examples in machine learning
-
A. 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.1
Langley, P.2
-
7
-
-
0026966646
-
A training algorithm for optimal margin classifiers
-
Pittsburgh, ACM
-
B. Boser, I. Guyon, and V. Vapnik. A training algorithm for optimal margin classifiers. In Fifth Annual Workshop on Computational Learning Theory, pages 144-152, Pittsburgh, 1992. ACM.
-
(1992)
Fifth Annual Workshop on Computational Learning Theory
, pp. 144-152
-
-
Boser, B.1
Guyon, I.2
Vapnik, V.3
-
8
-
-
0002709342
-
Feature selection via concave minimization and support vector machines
-
San Francisco, CA
-
P. S. Bradley and O. L. Mangasarian. Feature selection via concave minimization and support vector machines. In Proc. 13th ICML, pages 82-90, San Francisco, CA, 1998.
-
(1998)
Proc. 13th ICML
, pp. 82-90
-
-
Bradley, P.S.1
Mangasarian, O.L.2
-
9
-
-
0033721433
-
Massive data discrimination via linear support vector machines
-
P. S. Bradley and O. L. Mangasarian. Massive data discrimination via linear support vector machines. Optimization Methods and Software, 13(1):1-10, 2000. URL citeseer.nj.nec.com/bradley98massive.html.
-
(2000)
Optimization Methods and Software
, vol.13
, Issue.1
, pp. 1-10
-
-
Bradley, P.S.1
Mangasarian, O.L.2
-
10
-
-
0001010266
-
Feature selection via mathematical programming. Technical Report 95-21, Computer Sciences Department, University ofWisconsin, Madison,Wisconsin, 1995
-
P. S. Bradley, O. L. Mangasarian, and W. N. Street. Feature selection via mathematical programming. Technical Report 95-21, Computer Sciences Department, University ofWisconsin, Madison,Wisconsin, 1995. To appear in INFORMS Journal on Computing 10, 1998.
-
INFORMS Journal on Computing
, vol.10
, pp. 1998
-
-
Bradley, P.S.1
Mangasarian, O.L.2
Street, W.N.3
-
11
-
-
34249753618
-
Support vector networks
-
C. Cortes and V. Vapnik. Support vector networks. Machine Learning, 20:273 - 297, 1995.
-
(1995)
Machine Learning
, vol.20
, pp. 273-297
-
-
Cortes, C.1
Vapnik, V.2
-
14
-
-
0031624445
-
Large margin classification using the perceptron algorithm
-
Y. Freund and R. Schapire. Large margin classification using the perceptron algorithm. In COLT, 1998.
-
(1998)
COLT
-
-
Freund, Y.1
Schapire, R.2
-
15
-
-
84890523297
-
Minimal kernel classifiers. Technical Report DMI-00-08, Data Mining Institute, University of Wisconsin, Madison, 2000
-
G. Fung, O. L. Mangasarian, and A. J. Smola. Minimal kernel classifiers. Technical Report DMI-00-08, Data Mining Institute, University of Wisconsin, Madison, 2000. Submitted to IEEE Transactions on Pattern Analysis and Machine Intelligence.
-
IEEE Transactions on Pattern Analysis and Machine Intelligence
-
-
Fung, G.1
Mangasarian, O.L.2
Smola, A.J.3
-
17
-
-
0000963583
-
Linear and nonlinear separation of patterns by linear programming
-
O.L. Mangasarian. Linear and nonlinear separation of patterns by linear programming. Operations Research, 13:444-452, 1965.
-
(1965)
Operations Research
, vol.13
, pp. 444-452
-
-
Mangasarian, O.L.1
-
19
-
-
0001854616
-
Assessing relevance determination methods using delve
-
R. M. Neal. Assessing relevance determination methods using delve. Neural Networks and Machine Learning, pages 97-129, 1998.
-
(1998)
Neural Networks and Machine Learning
, pp. 97-129
-
-
Neal, R.M.1
-
23
-
-
11144273669
-
The perceptron: A probabilistic model for information storage and organization in the brain
-
F. Rosenblatt. The perceptron: A probabilistic model for information storage and organization in the brain. Psychological Review, 65(6):386-408, 1958.
-
(1958)
Psychological Review
, vol.65
, Issue.6
, pp. 386-408
-
-
Rosenblatt, F.1
-
26
-
-
0001224048
-
Sparse Bayesian learning and the relevance vector machine
-
M. E Tipping. Sparse Bayesian learning and the relevance vector machine. Journal of Machine Learning Research, 1:211-244, 2001.
-
(2001)
Journal of Machine Learning Research
, vol.1
, pp. 211-244
-
-
Tipping, M.E.1
-
31
-
-
84898948710
-
Feature selection for svms
-
Cambridge,MA. MIT Press
-
J. Weston, S. Mukherjee, O. Chapelle, M. Pontil, T. Poggio, and V. Vapnik. Feature selection for svms. In Neural Information Processing Systems, Cambridge,MA, 2001b. MIT Press.
-
(2001)
Neural Information Processing Systems
-
-
Weston, J.1
Mukherjee, S.2
Chapelle, O.3
Pontil, M.4
Poggio, T.5
Vapnik, V.6
-
32
-
-
0001254045
-
Multi-class support vector machines
-
M. Verleysen, editor, Brussels. D Facto
-
J. Weston and C. Watkins. Multi-class support vector machines. InM. Verleysen, editor, Proceedings ESANN, Brussels, 1999. D Facto.
-
(1999)
Proceedings ESANN
-
-
Weston, J.1
Watkins, C.2
|