-
1
-
-
0001199215
-
A general class of coefficients of divergence of one distribution from another
-
S.M. Ali and S.D. Silvey, "A general class of coefficients of divergence of one distribution from another," J. Royal Statistical Society (Series B), vol.28, no.1, pp.131-142, 1966.
-
(1966)
J. Royal Statistical Society (Series B)
, vol.28
, Issue.1
, pp. 131-142
-
-
Ali, S.M.1
Silvey, S.D.2
-
3
-
-
0003710380
-
-
Tech. Rep., Department of Computer Science, National Taiwan University
-
C.C. Chang and C.J. Lin, "LIBSVM: A library for support vector machines," Tech. Rep., Department of Computer Science, National Taiwan University, 2001. http://www.csie.ntu.edu.tw/?cjlin/libsvm/
-
(2001)
LIBSVM: A Library for Support Vector Machines
-
-
Chang, C.C.1
Lin, C.J.2
-
4
-
-
84889281816
-
-
2nd Ed. John Wiley & Sons, Hoboken, NJ, USA
-
T.M. Cover and J.A. Thomas, Elements of Information Theory, 2nd ed., John Wiley & Sons, Hoboken, NJ, USA, 2006.
-
(2006)
Elements Of Information Theory
-
-
Cover, T.M.1
Thomas, J.A.2
-
5
-
-
0000489740
-
Information-type measures of difference of probability distributions and indirect observation
-
I. Csisźar, "Information-type measures of difference of probability distributions and indirect observation," Studia Scientiarum Mathematicarum Hungarica, vol.2, pp.229-318, 1967.
-
(1967)
Studia Scientiarum Mathematicarum Hungarica
, vol.2
, pp. 229-318
-
-
Csisźar, I.1
-
6
-
-
56449092085
-
Efficient projections onto the-1-ball for learning in high dimensions
-
A. McCallum and S. Roweis
-
J. Duchi, S. Shalev-Shwartz, Y. Singer, and T. Chandra, "Efficient projections onto the-1-ball for learning in high dimensions," Proc. 25th Annual International Conference on Machine Learning (ICML 2008), ed. A. McCallum and S. Roweis, pp.272-279, 2008.
-
(2008)
Proc. 25th Annual International Conference on Machine Learning (ICML 2008)
, pp. 272-279
-
-
Duchi, J.1
Shalev-Shwartz, S.2
Singer, Y.3
Chandra, T.4
-
7
-
-
4544371135
-
Dimensionality reduction for supervised learning with reproducing kernel Hilbert spaces
-
K. Fukumizu, F.R. Bach, and M.I. Jordan, "Dimensionality reduction for supervised learning with reproducing kernel Hilbert spaces," J. Machine Learning Research, vol.5, no.1, pp.73-99, 2004.
-
(2004)
J. Machine Learning Research
, vol.5
, Issue.1
, pp. 73-99
-
-
Fukumizu, K.1
Bach, F.R.2
Jordan, M.I.3
-
8
-
-
33646528415
-
Measuring statistical dependence with Hilbert-Schmidt norms
-
ed. S. Jain, H.U. Simon, and E. Tomita, Lecture Notes in Artificial Intelligence, Berlin, Germany, Springer-Verlag
-
A. Gretton, O. Bousquet, A. Smola, and B. Scholkopf, "Measuring statistical dependence with Hilbert-Schmidt norms," Algorithmic Learning Theory, ed. S. Jain, H.U. Simon, and E. Tomita, Lecture Notes in Artificial Intelligence, Berlin, Germany, pp.63-77, Springer-Verlag, 2005.
-
(2005)
Algorithmic Learning Theory
, pp. 63-77
-
-
Gretton, A.1
Bousquet, O.2
Smola, A.3
Scholkopf, B.4
-
9
-
-
33745561205
-
An introduction to variable and feature selection
-
I. Guyon and A. Elisseeff, "An introduction to variable and feature selection," J.Machine Learning Research, vol.3, no.3, pp.1157-1182, 2003.
-
(2003)
J.Machine Learning Research
, vol.3
, Issue.3
, pp. 1157-1182
-
-
Guyon, I.1
Elisseeff, A.2
-
10
-
-
78049334876
-
Feature selection for reinforcement learning: Evaluating implicit state-reward dependency via conditional mutual information
-
Berlin Springer
-
H. Hachiya and M. Sugiyama, "Feature selection for reinforcement learning: Evaluating implicit state-reward dependency via conditional mutual information," Machine Learning and Knowledge Discovery in Databases, Part I, ed. J.L. Balc'azar, A.G.F. Bonchi, and M. Sebag, Lect. Notes Comput. Sci., vol.6321, Berlin, pp.474-489, Springer, 2010.
-
(2010)
Machine Learning and Knowledge Discovery in Databases, Part I, ed. J.L. Balc'azar, A.G.F. Bonchi, and M. Sebag, Lect. Notes Comput. Sci.
, vol.6321
, pp. 474-489
-
-
Hachiya, H.1
Sugiyama, M.2
-
11
-
-
85065703189
-
Correlation-based feature selection for discrete and numeric class machine learning
-
San Francisco, CA, USA
-
M.A. Hall, "Correlation-based feature selection for discrete and numeric class machine learning," Proc. Seventeenth International Conference on Machine Learning, pp.359-366, San Francisco, CA, USA, 2000.
-
(2000)
Proc. Seventeenth International Conference on Machine Learning
, pp. 359-366
-
-
Hall, M.A.1
-
12
-
-
84864039505
-
Laplacian score for feature selection
-
ed. Y. Weiss, B. Scholkopf, and J. Platt, MIT Press, Cambridge, MA
-
X. He, D. Cai, and P. Niyogi, "Laplacian score for feature selection," in Advances in Neural Information Processing Systems 18, ed. Y. Weiss, B. Scholkopf, and J. Platt, pp.507-514, MIT Press, Cambridge, MA, 2006.
-
(2006)
Advances in Neural Information Processing Systems
, vol.18
, pp. 507-514
-
-
He, X.1
Cai, D.2
Niyogi, P.3
-
13
-
-
85146422424
-
A practical approach to feature selection
-
San Francisco, CA, USA
-
K. Kira and L.A. Rendell, "A practical approach to feature selection," Proc. Ninth International Workshop on Machine Learning, pp.249-256, San Francisco, CA, USA, 1992.
-
(1992)
Proc. Ninth International Workshop on Machine Learning
, pp. 249-256
-
-
Kira, K.1
Rendell, L.A.2
-
14
-
-
0031381525
-
Wrappers for feature subset selection
-
R. Kohavi and G.H. John, "Wrappers for feature subset selection," Artif. Intell., vol.97, no.1, pp.273-324, 1997.
-
(1997)
Artif. Intell.
, vol.97
, Issue.1
, pp. 273-324
-
-
Kohavi, R.1
John, G.H.2
-
15
-
-
84992726552
-
Estimating attributes: Analysis and extensions of RELIEF
-
ed. F. Bergadano and L.D. Raedt, New York, NY, USA
-
I. Kononenko, "Estimating attributes: Analysis and extensions of RELIEF," European Conference on Machine Learning, ed. F. Bergadano and L.D. Raedt, pp.171-182, New York, NY, USA, 1994.
-
(1994)
European Conference on Machine Learning
, pp. 171-182
-
-
Kononenko, I.1
-
17
-
-
85061066913
-
Selection of relevant features in machine learning
-
Menlo Park, CA, USA
-
P. Langley, "Selection of relevant features in machine learning," Proc. AAAI Fall Symposium on Relevance, pp.140-144, Menlo Park, CA, USA, 1994.
-
(1994)
Proc. AAAI Fall Symposium on Relevance
, pp. 140-144
-
-
Langley, P.1
-
18
-
-
33750695296
-
Efficient L1 regularized logistic regression
-
S.I. Lee, H. Lee, P. Abbeel, and A.Y. Ng, "Efficient L1 regularized logistic regression," Proc. 21st National Conference on Artificial Intelligence (AAAI), pp.401-408, 2006.
-
(2006)
Proc. 21st National Conference on Artificial Intelligence (AAAI)
, pp. 401-408
-
-
Lee, S.I.1
Lee, H.2
Abbeel, P.3
Ng, A.Y.4
-
19
-
-
67649142447
-
From lasso regression to feature vector machine
-
ed. Y.Weiss, B. Scholkopf, and J. Platt, MIT Press, Cambridge, MA
-
F. Li, Y. Yang, and E. Xing, "From lasso regression to feature vector machine," in Advances in Neural Information Processing Systems 18, ed. Y.Weiss, B. Scholkopf, and J. Platt, pp.779-786, MIT Press, Cambridge, MA, 2006.
-
(2006)
Advances in Neural Information Processing Systems
, vol.18
, pp. 779-786
-
-
Li, F.1
Yang, Y.2
Xing, E.3
-
20
-
-
33947426775
-
On divergences and informations in statistics and information theory
-
F. Liese and I. Vajda, "On divergences and informations in statistics and information theory," IEEE Trans. Inf. Theory, vol.52, no.10, pp.4394-4412, 2006.
-
(2006)
IEEE Trans. Inf. Theory
, vol.52
, Issue.10
, pp. 4394-4412
-
-
Liese, F.1
Vajda, I.2
-
21
-
-
70350663114
-
Large-scale sparse logistic regression
-
New York, NY, USA
-
J. Liu, J. Chen, and J. Ye, "Large-scale sparse logistic regression," Proc. 15th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pp.547-556, New York, NY, USA, 2009.
-
(2009)
Proc. 15th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining
, pp. 547-556
-
-
Liu, J.1
Chen, J.2
Ye, J.3
-
22
-
-
77956531771
-
From transformation-based dimensionality reduction to feature selection
-
M. Masaeli, G. Fung, and J.G. Dy, "From transformation-based dimensionality reduction to feature selection," Proc. 27th International Conference on Machine Learning, pp.751-758, 2010.
-
(2010)
Proc. 27th International Conference on Machine Learning
, pp. 751-758
-
-
Masaeli, M.1
Fung, G.2
Dy, J.G.3
-
23
-
-
24344458137
-
Feature selection based on mutual information: Criteria of max-dependency, max-relevance, and minredundancy
-
H. Peng, F. Long, and C. Ding, "Feature selection based on mutual information: Criteria of max-dependency, max-relevance, and minredundancy," IEEE Trans. Pattern Anal. Mach. Intell., vol.27, no.8, pp.1226-1238, 2005.
-
(2005)
IEEE Trans. Pattern Anal. Mach. Intell.
, vol.27
, Issue.8
, pp. 1226-1238
-
-
Peng, H.1
Long, F.2
Ding, C.3
-
24
-
-
77951965521
-
Quadratic programming feature selection
-
Aug
-
I. Rodriguez-Lujan, R. Huerta, C. Elkan, and C.S. Cruz, "Quadratic programming feature selection," J. Machine Learning Research, vol.11, no.8, pp.1491-1516, Aug. 2010.
-
(2010)
J. Machine Learning Research
, vol.11
, Issue.8
, pp. 1491-1516
-
-
Rodriguez-Lujan, I.1
Huerta, R.2
Elkan, C.3
Cruz, C.S.4
-
25
-
-
35748932917
-
A review of feature selection techniques in bioinformatics
-
Y. Saeys, I. Inza, and P. Larranaga, "A review of feature selection techniques in bioinformatics," Bioinformatics, vol.23, no.19, pp.2507-2517, 2007.
-
(2007)
Bioinformatics
, vol.23
, Issue.19
, pp. 2507-2517
-
-
Saeys, Y.1
Inza, I.2
Larranaga, P.3
-
26
-
-
38049108135
-
Fast optimization methods for L1 regularization: A comparative study and two new approaches
-
M.W. Schmidt, G. Fung, and R. Rosales, "Fast optimization methods for L1 regularization: A comparative study and two new approaches," European Conference on Machine Learning, pp.286-297, 2007.
-
(2007)
European Conference on Machine Learning
, pp. 286-297
-
-
Schmidt, M.W.1
Fung, G.2
Rosales, R.3
-
27
-
-
0004094721
-
-
MIT Press, Cambridge, MA, USA
-
B. Scholkopf and A.J. Smola, Learning with Kernels, MIT Press, Cambridge, MA, USA, 2002.
-
(2002)
Learning with Kernels
-
-
Scholkopf, B.1
Smola, A.J.2
-
28
-
-
34547964410
-
Supervised feature selection via dependence estimation
-
L. Song, A. Smola, A. Gretton, K.M. Borgwardt, and J. Bedo, "Supervised feature selection via dependence estimation," Proc. 24th Annual International Conference on Machine Learning, pp.823-830, 2007.
-
(2007)
Proc. 24th Annual International Conference on Machine Learning
, pp. 823-830
-
-
Song, L.1
Smola, A.2
Gretton, A.3
Borgwardt, K.M.4
Bedo, J.5
-
29
-
-
0010786475
-
On the influence of the kernel on the consistency of support vector machines
-
Nov
-
I. Steinwart, "On the influence of the kernel on the consistency of support vector machines," J. Machine Learning Research, vol.2, pp.67-93, Nov. 2001.
-
(2001)
J. Machine Learning Research
, vol.2
, pp. 67-93
-
-
Steinwart, I.1
-
30
-
-
84877714816
-
Sufficient dimension reduction via squared-loss mutual information estimation
-
T. Suzuki and M. Sugiyama, "Sufficient dimension reduction via squared-loss mutual information estimation," Neural Comput., vol.25, no.3, pp.725-758, 2013.
-
(2013)
Neural Comput.
, vol.25
, Issue.3
, pp. 725-758
-
-
Suzuki, T.1
Sugiyama, M.2
-
31
-
-
67149113981
-
Approximating mutual information by maximum likelihood density ratio estimation
-
ed. Y. Saeys, H. Liu, I. Inza, L. Wehenkel, and Y.V. de Peer, JMLRWorkshop and Conference Proceedings, Antwerp, Belgium, Sept. 2008
-
T. Suzuki, M. Sugiyama, J. Sese, and T. Kanamori, "Approximating mutual information by maximum likelihood density ratio estimation," Proc. ECML-PKDD2008 Workshop on New Challenges for Feature Selection in Data Mining and Knowledge Discovery 2008 (FSDM2008), ed. Y. Saeys, H. Liu, I. Inza, L. Wehenkel, and Y.V. de Peer, JMLRWorkshop and Conference Proceedings, vol.4, pp.5-20, Antwerp, Belgium, Sept. 2008.
-
Proc. ECML-PKDD2008 Workshop on New Challenges for Feature Selection in Data Mining and Knowledge Discovery 2008 (FSDM2008)
, vol.4
, pp. 5-20
-
-
Suzuki, T.1
Sugiyama, M.2
Sese, J.3
Kanamori, T.4
-
32
-
-
78650608280
-
Least-squares independent component analysis
-
T. Suzuki andM. Sugiyama, "Least-squares independent component analysis," Neural Comput., vol.23, no.1, pp.284-301, 2011.
-
(2011)
Neural Comput.
, vol.23
, Issue.1
, pp. 284-301
-
-
Suzuki, T.1
Sugiyama, M.2
-
33
-
-
60849121715
-
Mutual information estimation reveals global associations between stimuli and biological processes
-
T. Suzuki, M. Sugiyama, T. Kanamori, and J. Sese, "Mutual information estimation reveals global associations between stimuli and biological processes," BMC Bioinformatics, vol.10, no.S-1, p.S52, 2009.
-
(2009)
BMC Bioinformatics
, vol.10
-
-
Suzuki, T.1
Sugiyama, M.2
Kanamori, T.3
Sese, J.4
-
34
-
-
85194972808
-
Regression shrinkage and selection via the lasso
-
R. Tibshirani, "Regression shrinkage and selection via the lasso," J. Royal Statistical Society (Series B), vol.58, no.1, pp.267-288, 1996.
-
(1996)
J. Royal Statistical Society (Series B)
, vol.58
, Issue.1
, pp. 267-288
-
-
Tibshirani, R.1
-
35
-
-
1942450610
-
Feature extraction by non-parametric mutual information maximization
-
March
-
K. Torkkola, "Feature extraction by non-parametric mutual information maximization," J. Machine Learning Research, vol.3, no.3, pp.1415-1438, March 2003.
-
(2003)
J. Machine Learning Research
, vol.3
, Issue.3
, pp. 1415-1438
-
-
Torkkola, K.1
-
36
-
-
84890520049
-
Use of the zero norm with linear models and kernel methods
-
March
-
J. Weston, A. Elisseeff, B. Scholkopf, and M. Tipping, "Use of the zero norm with linear models and kernel methods," J. Machine Learning Research, vol.3, no.3, pp.1439-1461, March 2003.
-
(2003)
J. Machine Learning Research
, vol.3
, Issue.3
, pp. 1439-1461
-
-
Weston, J.1
Elisseeff, A.2
Scholkopf, B.3
Tipping, M.4
-
37
-
-
34547981441
-
Spectral feature selection for supervised and unsupervised learning
-
New York, NY, USA
-
Z. Zhao and H. Liu, "Spectral feature selection for supervised and unsupervised learning," Proc. 24th International Conference on Machine Learning, pp.1151-1157, New York, NY, USA, 2007.
-
(2007)
Proc. 24th International Conference on Machine Learning
, pp. 1151-1157
-
-
Zhao, Z.1
Liu, H.2
-
38
-
-
77958565426
-
Efficient spectral feature selection with minimum redundancy
-
Z. Zhao, L. Wang, and H. Liu, "Efficient spectral feature selection with minimum redundancy," Proc. Twenty-Fourth AAAI Conference on Artificial Intelligence, pp.673-678, 2010.
-
(2010)
Proc. Twenty-Fourth AAAI Conference on Artificial Intelligence
, pp. 673-678
-
-
Zhao, Z.1
Wang, L.2
Liu, H.3
-
39
-
-
84899024917
-
1-norm support vector machines
-
ed. S. Thrun, L. Saul, and B. Scholkopf, MIT Press, Cambridge, MA, USA
-
J. Zhu, S. Rosset, T. Hastie, and R. Tibshirani, "1-norm support vector machines," in Advances in Neural Information Processing Systems 16, ed. S. Thrun, L. Saul, and B. Scholkopf, MIT Press, Cambridge, MA, USA, 2004.
-
(2004)
Advances in Neural Information Processing Systems
, vol.16
-
-
Zhu, J.1
Rosset, S.2
Hastie, T.3
Tibshirani, R.4
|