-
1
-
-
33745561205
-
An introduction to variable selection and feature selection
-
I. Guyon and A. Elisseeff, "An introduction to variable selection and feature selection," Journal of Machine Learning Research, vol. 3, pp. 1157-1182, 2003.
-
(2003)
Journal of Machine Learning Research
, vol.3
, pp. 1157-1182
-
-
Guyon, I.1
Elisseeff, A.2
-
2
-
-
0003684449
-
-
New York: Springer-Verlag
-
T. Hastie, R. Tibshirani, and J. H. Friedman, The elements of statistical learning: data mining, inference, and prediction, New York: Springer-Verlag, 2001.
-
(2001)
The Elements of Statistical Learning: Data Mining, Inference, and Prediction
-
-
Hastie, T.1
Tibshirani, R.2
Friedman, J.H.3
-
3
-
-
84891283756
-
Nonnegative matrix and tensor factorizations
-
Wiley, Chichester
-
Andrzej A. Cichocki, A. H. Phan, and R. Zdunek, Nonnegative Matrix and Tensor Factorizations: Applications to Exploratory Multi-way Data Analysis and Blind Source Separation, Wiley, Chichester, 2009.
-
(2009)
Applications to Exploratory Multi-way Data Analysis and Blind Source Separation
-
-
Cichocki, A.A.1
Phan, A.H.2
Zdunek, R.3
-
4
-
-
68649096448
-
Tensor decompositions and applications
-
T. G. Kolda and B. W. Bader, "Tensor decompositions and applications," SIAMReview, vol. 51, no. 3, pp. 455-500, 2009.
-
(2009)
SIAMReview
, vol.51
, Issue.3
, pp. 455-500
-
-
Kolda, T.G.1
Bader, B.W.2
-
5
-
-
51649131593
-
Extracting the optimal dimensionality for local tensor discriminant analysis
-
Jan.
-
F. Nie, S. Xiang, Y. Song, and C. Zhang, "Extracting the optimal dimensionality for local tensor discriminant analysis," Pattern Recognition, vol. 42, no. 1, pp. 105-114, Jan. 2009.
-
(2009)
Pattern Recognition
, vol.42
, Issue.1
, pp. 105-114
-
-
Nie, F.1
Xiang, S.2
Song, Y.3
Zhang, C.4
-
6
-
-
78751515806
-
Tensor decompositions for feature extraction and classification of high dimensional datasets
-
H. A. Phan and A. Cichocki, "Tensor decompositions for feature extraction and classification of high dimensional datasets," Nonlinear Theory and Its Applications, IEICE, vol. 1, no. 1, pp. 37-68, 2010.
-
(2010)
Nonlinear Theory and Its Applications, IEICE
, vol.1
, Issue.1
, pp. 37-68
-
-
Phan, H.A.1
Cichocki, A.2
-
7
-
-
84870525911
-
Benefits of multi-domain feature of mismatch negativity extracted by non-negative tensor factorization from eeg collected by low-density array
-
F. Cong, A. H. Phan, Q. Zhao, T. Huttunen-Scott, J. Kaartinen, T. Ristaniemi, H. Lyytinen, and A. Cichocki, "Benefits of multi-domain feature of mismatch negativity extracted by non-negative tensor factorization from eeg collected by low-density array," Int. J. Neural Syst., vol. 22, no. 6, 2012.
-
(2012)
Int. J. Neural Syst.
, vol.22
, Issue.6
-
-
Cong, F.1
Phan, A.H.2
Zhao, Q.3
Huttunen-Scott, T.4
Kaartinen, J.5
Ristaniemi, T.6
Lyytinen, H.7
Cichocki, A.8
-
9
-
-
78149456734
-
A factorization method for the classification of infrared spectra
-
Carsten Henneges, Pavel Laskov, Endang Darmawan, Jürgen Backhaus, Bernd Kammerer, and Andreas Zell, "A factorization method for the classification of infrared spectra," BMC Bioinformatics, vol. 11, no. 1, pp. 561, 2010.
-
(2010)
BMC Bioinformatics
, vol.11
, Issue.1
, pp. 561
-
-
Henneges, C.1
Laskov, P.2
Darmawan, E.3
Backhaus, J.4
Kammerer, B.5
Zell, A.6
-
10
-
-
84855185917
-
A mixture model with a reference-based automatic selection of components for disease classification from protein and/or gene expression levels
-
Ivica Kopriva and Marko Filipovíc, "A mixture model with a reference-based automatic selection of components for disease classification from protein and/or gene expression levels," BMC Bioinformatics, vol. 12, pp. 496, 2011.
-
(2011)
BMC Bioinformatics
, vol.12
, pp. 496
-
-
Kopriva, I.1
Filipovíc, M.2
-
11
-
-
85162707890
-
The expression of a tensor or a polyadic as a sum of products
-
F. L. Hitchcock, "The expression of a tensor or a polyadic as a sum of products," Journal of Mathematics and Physics, no. 7, pp. 164-189, 1927.
-
(1927)
Journal of Mathematics and Physics
, Issue.7
, pp. 164-189
-
-
Hitchcock, F.L.1
-
12
-
-
48749101457
-
Three-way arrays: Rank and uniqueness of trilinear decompositions, with application to arithmetic complexity and statistics
-
J Kruskal, "Three-way arrays: rank and uniqueness of trilinear decompositions, with application to arithmetic complexity and statistics," Linear Algebra and Its Applications, vol. 18, pp. 95-138, 1977.
-
(1977)
Linear Algebra and Its Applications
, vol.18
, pp. 95-138
-
-
Kruskal, J.1
-
13
-
-
1942450610
-
Feature extraction by non-parametricmutual informationmaximization
-
K. Torkkola, "Feature extraction by non-parametricmutual informationmaximization," Journal ofMachine Learning Research, vol. 3, pp. 1415-1438, 2003.
-
(2003)
Journal OfMachine Learning Research
, vol.3
, pp. 1415-1438
-
-
Torkkola, K.1
-
14
-
-
34548656483
-
Maximization of mutual information for supervised linear feature extraction
-
J. M. Leiva-Murillo and A. Artès-Rodr̀gues, "Maximization of mutual information for supervised linear feature extraction," IEEE Transactions on Neural Networks, vol. 18, no. 5, pp. 1433-1441, 2007.
-
(2007)
IEEE Transactions on Neural Networks
, vol.18
, Issue.5
, pp. 1433-1441
-
-
Leiva-Murillo, J.M.1
Artès-Rodrgues, A.2
-
15
-
-
84857419890
-
Task-driven dictionary learning
-
J. Mairal, F. Bach, and J. Ponce, "Task-driven dictionary learning," IEEE Transactions on Pattern Analysis and Machine Intelligence, pp. 791-804, 2012.
-
(2012)
IEEE Transactions on Pattern Analysis and Machine Intelligence
, pp. 791-804
-
-
Mairal, J.1
Bach, F.2
Ponce, J.3
-
16
-
-
30144444694
-
A comparison of algorithms for fitting the PARAFAC model
-
G. Tomasi and R. Bro, "A comparison of algorithms for fitting the PARAFAC model," Computational Statistics & Data Analysis, vol. 50, no. 7, pp. 1700-1734, 2006.
-
(2006)
Computational Statistics & Data Analysis
, vol.50
, Issue.7
, pp. 1700-1734
-
-
Tomasi, G.1
Bro, R.2
-
17
-
-
0038685059
-
A new efficient method for determining the number of components in PARAFAC models
-
R. Bro and H. A. L. Kiers, "A new efficient method for determining the number of components in PARAFAC models," Journal of Chemometrics, vol. 17, pp. 274-286, 2002.
-
(2002)
Journal of Chemometrics
, vol.17
, pp. 274-286
-
-
Bro, R.1
Kiers, H.A.L.2
-
21
-
-
84901317456
-
-
Center for Cancer Research, National Cancer Institute
-
Center for Cancer Research, National Cancer Institute, "Clinical Proteomics Program," Available online.
-
Clinical Proteomics Program
-
-
-
22
-
-
0037120949
-
Serum proteomic patterns for detection of prostate cancer
-
E. F. Petricoin et al., "Serum proteomic patterns for detection of prostate cancer," Journal of the National Cancer Institute, vol. 94, no. 20, pp. 1576-1578, 2002.
-
(2002)
Journal of the National Cancer Institute
, vol.94
, Issue.20
, pp. 1576-1578
-
-
Petricoin, E.F.1
-
24
-
-
0037116832
-
Use of proteomic patterns in serum to identify ovarian cancer
-
E. F. Petricoin et al., "Use of proteomic patterns in serum to identify ovarian cancer," The Lancet, no. 359, pp. 572-577, 2002.
-
(2002)
The Lancet
, Issue.359
, pp. 572-577
-
-
Petricoin, E.F.1
-
25
-
-
3543076921
-
Application of the GA/KNN method to SELDI proteomics data
-
L. Li et al., "Application of the GA/KNN method to SELDI proteomics data," Bioinformatics, vol. 20, no. 10, pp. 1638-1640, 2003.
-
(2003)
Bioinformatics
, vol.20
, Issue.10
, pp. 1638-1640
-
-
Li, L.1
|