-
1
-
-
0033536012
-
Broad patterns of gene expression revealed by clustering analysis of tumor and normal colon tissues probed by oligonucleotide arrays
-
June
-
Alon, U., Barkai, N., Notterman, D. A., Gishdagger, K., Ybarradagger, S., Mackdagger, D. and Levine, A. J. Broad patterns of gene expression revealed by clustering analysis of tumor and normal colon tissues probed by oligonucleotide arrays. In Proc. of the Nat. Ac. of Sc. of the USA, pp. 6745-6750, June 1999.
-
(1999)
Proc. of the Nat. Ac. of Sc. of the USA
, pp. 6745-6750
-
-
Alon, U.1
Barkai, N.2
Notterman, D.A.3
Gishdagger, K.4
Ybarradagger, S.5
Mackdagger, D.6
Levine, A.J.7
-
2
-
-
0036568025
-
Finite-time analysis of the Multiarmed Bandit problem
-
Auer, P., Cesa-Bianchi, N. and Fischer, P. Finite-time analysis of the Multiarmed Bandit problem. Mach. Learn., 47(2-3):235-256, 2002.
-
(2002)
Mach. Learn.
, vol.47
, Issue.2-3
, pp. 235-256
-
-
Auer, P.1
Cesa-Bianchi, N.2
Fischer, P.3
-
3
-
-
84858766876
-
Exploring large feature spaces with Hierarchical multiple kernel learning
-
Bach, F. Exploring large feature spaces with Hierarchical Multiple Kernel Learning. In NIPS'08, pp. 105-112, 2008.
-
(2008)
NIPS'08
, pp. 105-112
-
-
Bach, F.1
-
5
-
-
34547688866
-
Compression-based averaging of selective Naive Bayes classifiers
-
Boullé, M. Compression-based averaging of selective Naive Bayes classifiers. J. Mach. Learn. Res., 8:1659-1685, 2007.
-
(2007)
J. Mach. Learn. Res.
, vol.8
, pp. 1659-1685
-
-
Boullé, M.1
-
6
-
-
0003802343
-
-
Taylor & Francis, Inc
-
Breiman, L., Friedman, J., Stone, C. J. and Olshen, R.A. Classification and Regression Trees. Taylor & Francis, Inc., 1984.
-
(1984)
Classification and Regression Trees
-
-
Breiman, L.1
Friedman, J.2
Stone, C.J.3
Olshen, R.A.4
-
7
-
-
34547971383
-
Direct convex relaxations of sparse SVM
-
DOI 10.1145/1273496.1273515, Proceedings, Twenty-Fourth International Conference on Machine Learning, ICML 2007
-
Chan, A. B., Vasconcelos, N. and Lanckriet, G. R. G. Direct convex relaxations of sparse SVM. In ICML'01, pp. 145-153, 2007. (Pubitemid 47275060)
-
(2007)
ACM International Conference Proceeding Series
, vol.227
, pp. 145-153
-
-
Chan, A.B.1
Vasconcelos, N.2
Lanckriet, G.R.G.3
-
8
-
-
5044234815
-
Torch: A modular machine learning software library
-
Collobert, R., Bengio, S. and Marithoz, J. Torch: A modular machine learning software library. Technical report, IDIAP, 2002.
-
(2002)
Technical Report, IDIAP
-
-
Collobert, R.1
Bengio, S.2
Marithoz, J.3
-
9
-
-
38049037928
-
Efficient selectivity and backup operators in Monte-carlo tree search
-
Coulom, R. Efficient selectivity and backup operators in Monte-Carlo tree search. In Computers and Games, pp. 72-83, 2006.
-
(2006)
Computers and Games
, pp. 72-83
-
-
Coulom, R.1
-
10
-
-
71149107214
-
Bandit-based optimization on graphs with application to library performance tuning
-
de Mesmay, F., Rimmel, A., Voronenko, Y. and Püschel, M. Bandit-based optimization on graphs with application to library performance tuning. In ICML'09, pp. 729-736, 2009.
-
(2009)
ICML'09
, pp. 729-736
-
-
De Mesmay, F.1
Rimmel, A.2
Voronenko, Y.3
Püschel, M.4
-
11
-
-
3242708140
-
Least angle regression
-
Efron, B., Hastie, T., Johnstone, I. and Tibshirani, R. Least angle regression. Annals of Statistics, 32:407-499, 2004.
-
(2004)
Annals of Statistics
, vol.32
, pp. 407-499
-
-
Efron, B.1
Hastie, T.2
Johnstone, I.3
Tibshirani, R.4
-
12
-
-
0034592781
-
Data selection for support vector machine classifiers
-
Fung, G. and Mangasarian, O. L. Data Selection for Support Vector Machine Classifiers. In KDD'00, pp. 64-70, 2000.
-
(2000)
KDD'00
, pp. 64-70
-
-
Fung, G.1
Mangasarian, O.L.2
-
13
-
-
34547990649
-
Combining online and offline knowledge in UCT
-
Gelly, S. and Silver, D. Combining online and offline knowledge in UCT. In ICML'07, pp. 273-280, 2007.
-
(2007)
ICML'07
, pp. 273-280
-
-
Gelly, S.1
Silver, D.2
-
14
-
-
0036161259
-
Gene selection for cancer classification using support vector machines
-
Guyon, I., Weston, J., Barnhill, S. and Vapnik, V. Gene selection for cancer classification using Support Vector Machines. Mach. Learn., 46(1-3):389-422, 2002.
-
(2002)
Mach. Learn.
, vol.46
, Issue.1-3
, pp. 389-422
-
-
Guyon, I.1
Weston, J.2
Barnhill, S.3
Vapnik, V.4
-
15
-
-
33646391384
-
Result analysis of the NIPS 2003 feature selection challenge
-
Guyon, I., Gunn, S. R., Ben-Hur, A. and Dror, G. Result analysis of the NIPS 2003 Feature Selection challenge. In NIPS'04, pp. 545-552, 2004.
-
(2004)
NIPS'04
, pp. 545-552
-
-
Guyon, I.1
Gunn, S.R.2
Ben-Hur, A.3
Dror, G.4
-
16
-
-
34250885083
-
Competitive baseline methods set new standards for the NIPS 2003 feature selection bench-mark
-
Guyon, I., Li, J., Maxier, T., Pletscher, P. A., Schneider, G. and Uhr, M. Competitive baseline methods set new standards for the NIPS 2003 feature selection benchmark. Pattern Recogn. Lett, 28(12): 1438-1444, 2007.
-
(2007)
Pattern Recogn. Lett
, vol.28
, Issue.12
, pp. 1438-1444
-
-
Guyon, I.1
Li, J.2
Maxier, T.3
Pletscher, P.A.4
Schneider, G.5
Uhr, M.6
-
17
-
-
85065703189
-
Correlation-based Feature Selection for discrete and numeric class Machine Learning
-
Hall, M. A. Correlation-based Feature Selection for discrete and numeric class Machine Learning. In ICML '00, pp. 359-366, 2000.
-
(2000)
ICML '00
, pp. 359-366
-
-
Hall, M.A.1
-
18
-
-
71149092858
-
Partially supervised Feature Selection with regularized linear models
-
Helleputte, T. and Dupont, P. Partially supervised Feature Selection with regularized linear models. In ICML'09, pp. 409-416, 2009.
-
(2009)
ICML'09
, pp. 409-416
-
-
Helleputte, T.1
Dupont, P.2
-
19
-
-
85146422424
-
A practical approach to feature selection
-
Kira, K. and Rendeli, L. A. A practical approach to feature selection. In ML '92, pp. 249-256, 1992.
-
(1992)
ML '92
, pp. 249-256
-
-
Kira, K.1
Rendeli, L.A.2
-
20
-
-
33750293964
-
Bandit based Monte-Carlo planning
-
Kocsis, L. and Szepesvári, C. Bandit based Monte-Carlo planning. In ECML'06, pp. 282-293, 2006.
-
(2006)
ECML'06
, pp. 282-293
-
-
Kocsis, L.1
Szepesvári, C.2
-
21
-
-
77956496569
-
Toward provably correct feature selection in arbitrary domains
-
Margaritis, D. Toward provably correct Feature Selection in arbitrary domains. In NIPS'09, pp. 1240-1248, 2009.
-
(2009)
NIPS'09
, pp. 1240-1248
-
-
Margaritis, D.1
-
22
-
-
33745834365
-
Identifying feature relevance using a Random Forest
-
Rogers, J. and Gunn, S. R. Identifying feature relevance using a Random Forest. In SLSFS, pp. 173-184, 2005.
-
(2005)
SLSFS
, pp. 173-184
-
-
Rogers, J.1
Gunn, S.R.2
-
23
-
-
70349956665
-
Boosting active learning to optimality: A tractable Monte-Carlo, Billiard-based algorithm
-
Rolet, P., Sebag, M., and Teytaud, O. Boosting Active Learning to optimality: a tractable Monte-Carlo, Billiard-based algorithm. In ECML'09, pp. 302-317, 2009.
-
(2009)
ECML'09
, pp. 302-317
-
-
Rolet, P.1
Sebag, M.2
Teytaud, O.3
-
24
-
-
36849082989
-
Feature selection via sensitivity analysis of SVM probabilistic outputs
-
Shen, K. Q., Ong, C. J., Li, X. P. and Wilder-Smith, E. P. V. Feature selection via sensitivity analysis of SVM probabilistic outputs. Mach. Learn., 70(1): 1-20, 2008.
-
(2008)
Mach. Learn.
, vol.70
, Issue.1
, pp. 1-20
-
-
Shen, K.Q.1
Ong, C.J.2
Li, X.P.3
Wilder-Smith, E.P.V.4
-
25
-
-
85194972808
-
Regression shrinkage and selection via the Lasso
-
Series B
-
Tibshirani, R. Regression shrinkage and selection via the Lasso. Journal of the Royal Statistical Society, Series B, 58:267-288, 1994.
-
(1994)
Journal of the Royal Statistical Society
, vol.58
, pp. 267-288
-
-
Tibshirani, R.1
-
26
-
-
71149100224
-
More generality in efficient Multiple Kernel Learning
-
Varrna, M. and Babu, B. R. More generality in efficient Multiple Kernel Learning. In ICML'09, pp. 1065-1072, 2009.
-
(2009)
ICML'09
, pp. 1065-1072
-
-
Varrna, M.1
Babu, B.R.2
-
27
-
-
84863381440
-
Algorithms for infinitely Many-armed Bandits
-
Wang, Y., Audibert, J.Y. and Munos, R. Algorithms for infinitely Many-Armed Bandits. In NIPS08, pp. 1729-1736, 2008.
-
(2008)
NIPS08
, pp. 1729-1736
-
-
Wang, Y.1
Audibert, J.Y.2
Munos, R.3
-
28
-
-
84863393425
-
Adaptive forward-backward greedy algorithm for sparse learning with linear models
-
Zhang, T. Adaptive Forward-Backward Greedy Algorithm for Sparse Learning with Linear Models. In NIPS'08, pp. 1921-1928, 2008a.
-
(2008)
NIPS'08
, pp. 1921-1928
-
-
Zhang, T.1
-
29
-
-
84863420367
-
Multi-stage convex relaxation for learning with sparse regularization
-
Zhang, T. Multi-stage Convex Relaxation for Learning with Sparse Regularization. In NIPS'08, pp. 1929-1936, 2008b.
-
(2008)
NIPS'08
, pp. 1929-1936
-
-
Zhang, T.1
|