-
1
-
-
85196057302
-
-
Rank-based distance metric learning: an application to image retrieval, In Proceedings of IEEE Computer Society Conference on Computer Vision and Pattern Recognition
-
J.-E. Lee, R. Jin, and A. K. Jain, Rank-based distance metric learning: an application to image retrieval, In Proceedings of IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2008, 1-8.
-
(2008)
, pp. 1-8
-
-
Lee, J.-E.1
Jin, R.2
Jain, A.K.3
-
2
-
-
24644436425
-
-
Learning a similarity metric discriminatively, with application to face verification, In Proceedings of IEEE Computer Society Conference on Computer Vision and Pattern Recognition
-
S. Chopra, R. Hadsell, and Y. LeCun, Learning a similarity metric discriminatively, with application to face verification, In Proceedings of IEEE Computer Society Conference on Computer Vision and Pattern Recognition, Vol. 1, 2005, 539-546.
-
(2005)
, vol.1
, pp. 539-546
-
-
Chopra, S.1
Hadsell, R.2
LeCun, Y.3
-
3
-
-
33746131974
-
Kernel-based distance metric learning for microarray data classification
-
H. Xiong and X. Chen, Kernel-based distance metric learning for microarray data classification, BMC Bioinformatics 7 (2006), 299.
-
(2006)
BMC Bioinformatics
, vol.7
, pp. 299
-
-
Xiong, H.1
Chen, X.2
-
4
-
-
84964989291
-
-
Predicting patient's trajectory of physiological data using temporal trends in similar patients: A system for near-term prognostics, In AMIA Annual Symposium Proceedings
-
S. Ebadollahi, J. Sun, D. Gotz, J. Hu, D. Sow, and C. Neti, Predicting patient's trajectory of physiological data using temporal trends in similar patients: A system for near-term prognostics, In AMIA Annual Symposium Proceedings, 2010, 192-196.
-
(2010)
, pp. 192-196
-
-
Ebadollahi, S.1
Sun, J.2
Gotz, D.3
Hu, J.4
Sow, D.5
Neti, C.6
-
5
-
-
78149476267
-
-
Localized supervised metric learning on temporal physiological data, In Proceedings of the International Conference on Pattern Recognition (ICPR)
-
J. Sun, D. Sow, J. Hu, and S. Ebadollahi, Localized supervised metric learning on temporal physiological data, In Proceedings of the International Conference on Pattern Recognition (ICPR), 2010, 4149-4152.
-
(2010)
, pp. 4149-4152
-
-
Sun, J.1
Sow, D.2
Hu, J.3
Ebadollahi, S.4
-
6
-
-
85196054864
-
-
Distance metric learning: A comprehensive survey, Technical report, Department of Computer Science and Engineering, Michigan State University
-
L. Yang, Distance metric learning: A comprehensive survey, Technical report, Department of Computer Science and Engineering, Michigan State University, 2006.
-
(2006)
-
-
Yang, L.1
-
8
-
-
85032996208
-
Stochastic neighbor embedding
-
Cambridge, MA, MIT Press
-
G. Hinton and S. Roweis, Stochastic neighbor embedding, Advances in Neural Information Processing Systems 15, Cambridge, MA, MIT Press, 2002, 833-840.
-
(2002)
Advances in Neural Information Processing Systems 15
, pp. 833-840
-
-
Hinton, G.1
Roweis, S.2
-
10
-
-
70349246930
-
-
Semi-supervised metric learning by maximizing constraint margin, In Proceedings of ACM 17th Conference on Information and Knowledge Management
-
F. Wang, S. Chen, T. Li, and C. Zhang, Semi-supervised metric learning by maximizing constraint margin, In Proceedings of ACM 17th Conference on Information and Knowledge Management, 2008, 1457-1458.
-
(2008)
, pp. 1457-1458
-
-
Wang, F.1
Chen, S.2
Li, T.3
Zhang, C.4
-
11
-
-
85196069439
-
-
Distance metric learning with application to clustering with side-information, In Advances in Neural Information Processing System 15
-
E. Xing, A. Ng, M. Jordan, and S. Russell, Distance metric learning with application to clustering with side-information, In Advances in Neural Information Processing System 15, 2003, 505-512.
-
(2003)
, pp. 505-512
-
-
Xing, E.1
Ng, A.2
Jordan, M.3
Russell, S.4
-
12
-
-
0003922190
-
-
2nd ed.), New York, NY, Wiley Interscience
-
R. O. Duda, P. E. Hart, and D. H. Stork, Pattern Classification (2nd ed.), New York, NY, Wiley Interscience, 2000.
-
(2000)
Pattern Classification
-
-
Duda, R.O.1
Hart, P.E.2
Stork, D.H.3
-
13
-
-
85196123116
-
-
Neighbourhood component analysis, In Advances in Neural Information Processing Systems 17
-
J. Goldberger, S. Roweis, G. Hinton, and R. Salakhutdinov, Neighbourhood component analysis, In Advances in Neural Information Processing Systems 17, 2005, 513-520.
-
(2005)
, pp. 513-520
-
-
Goldberger, J.1
Roweis, S.2
Hinton, G.3
Salakhutdinov, R.4
-
14
-
-
61749090884
-
Distance metric learning for large margin nearest neighbor classification
-
K. Q. Weinberger and L. K. Saul, Distance metric learning for large margin nearest neighbor classification, J Mach Learn Res 10 (2009), 207-244.
-
(2009)
J Mach Learn Res
, vol.10
, pp. 207-244
-
-
Weinberger, K.Q.1
Saul, L.K.2
-
15
-
-
84887916087
-
Regularized discriminant analysis
-
405) ()
-
J. H. Friedman, Regularized discriminant analysis, J Am Stat Assoc 84(405) (1989), 165-175.
-
(1989)
J Am Stat Assoc
, vol.84
, pp. 165-175
-
-
Friedman, J.H.1
-
16
-
-
33745743918
-
-
Computational and theoretical analysis of null space and orthogonal linear discriminant analysis,
-
J. Ye and T. Xiong, Computational and theoretical analysis of null space and orthogonal linear discriminant analysis, Vol. 7, 2006, 1183-1204.
-
(2006)
, vol.7
, pp. 1183-1204
-
-
Ye, J.1
Xiong, T.2
-
18
-
-
84880899766
-
-
Locality sensitive discriminant analysis, In Proceedings of the 20th International Joint Conference on Artificial Intelligence
-
D. Cai, X. He, K. Zhou, J. Han, and H. Bao, Locality sensitive discriminant analysis, In Proceedings of the 20th International Joint Conference on Artificial Intelligence, 2007. 708-713.
-
(2007)
, pp. 708-713
-
-
Cai, D.1
He, X.2
Zhou, K.3
Han, J.4
Bao, H.5
-
19
-
-
8844278523
-
Learning the kernel matrix with semidefinite programming
-
G. R. G. Lanckriet, N. Cristianini, P. Bartlett, L. El Ghaoui, and M. I. Jordan, Learning the kernel matrix with semidefinite programming, J Mach Learn Res 5 (2004), 27-72.
-
(2004)
J Mach Learn Res
, vol.5
, pp. 27-72
-
-
Lanckriet, G.R.G.1
Cristianini, N.2
Bartlett, P.3
El Ghaoui, L.4
Jordan, M.I.5
-
20
-
-
85196120843
-
-
Multiple kernel learning, conic duality, and the smo algorithm, In Proceedings of International Conference on Machine Learning
-
F. R. Bach, G. R. G. Lanckriet, and M. I. Jordan, Multiple kernel learning, conic duality, and the smo algorithm, In Proceedings of International Conference on Machine Learning, 2004, 6-13.
-
(2004)
, pp. 6-13
-
-
Bach, F.R.1
Lanckriet, G.R.G.2
Jordan, M.I.3
-
21
-
-
33745776113
-
Large scale multiple kernel learning
-
S. Sonnenburg, G. Rätsch, C. Schäfer, and B. Schölkopf, Large scale multiple kernel learning, J Mach Learn Res 7 (2006), 1531-1565.
-
(2006)
J Mach Learn Res
, vol.7
, pp. 1531-1565
-
-
Sonnenburg, S.1
Rätsch, G.2
Schäfer, C.3
Schölkopf, B.4
-
22
-
-
84858743760
-
Learning non-linear combinations of kernels
-
In, eds., Cambridge, MA, MIT Press
-
C. Cortes, M. Mohri, and A. Rostamizadeh, Learning non-linear combinations of kernels, In Advances in Neural Information Processing Systems 22, Y. Bengio, D. Schuurmans, J. Lafferty, C. K. I. Williams, and A. Culotta, eds., Cambridge, MA, MIT Press, 2009, 396-404.
-
(2009)
Advances in Neural Information Processing Systems 22
, pp. 396-404
-
-
Cortes, C.1
Mohri, M.2
Rostamizadeh, A.3
Bengio, Y.4
Schuurmans, D.5
Lafferty, J.6
Williams, C.K.I.7
Culotta, A.8
-
23
-
-
85196085068
-
-
Two-layer multiple kernel learning, In Proceedings of the 14th International Conference on Artificial Intelligence and Statistics, Journal of Machine Learning Research W & CPs
-
J. Zhuang, I. W. Tsang, and S. C. Hoi, Two-layer multiple kernel learning, In Proceedings of the 14th International Conference on Artificial Intelligence and Statistics, Journal of Machine Learning Research W & CPs, Vol. 15, 2011.
-
(2011)
, vol.15
-
-
Zhuang, J.1
Tsang, I.W.2
Hoi, S.C.3
-
24
-
-
0030211964
-
Bagging predictors
-
2) ()
-
L. Breiman, Bagging predictors, Mach Learn 24(2) (1996), 123-140.
-
(1996)
Mach Learn
, vol.24
, pp. 123-140
-
-
Breiman, L.1
-
25
-
-
84983110889
-
-
A decision-theoretic generalization of on-line learning and an application to boosting, In European Conference on Computational Learning Theory
-
Y. Freund and R. E. Schapire, A decision-theoretic generalization of on-line learning and an application to boosting, In European Conference on Computational Learning Theory, 1995. 23-37.
-
(1995)
, pp. 23-37
-
-
Freund, Y.1
Schapire, R.E.2
-
27
-
-
63449119775
-
-
New York, NY, Springer
-
J. Vaidya, C. Clifton, and M. Zhu, Privacy Preserving Data Mining, New York, NY, Springer, 2005.
-
(2005)
Privacy Preserving Data Mining
-
-
Vaidya, J.1
Clifton, C.2
Zhu, M.3
-
28
-
-
77951197218
-
-
Two heads better than one: metric+active learning and its applications for it service classification, In IEEE International Conference on Data Mining
-
F. Wang, J. Sun, T. Li, and N. Anerousis, Two heads better than one: metric+active learning and its applications for it service classification, In IEEE International Conference on Data Mining, 2009, 1022-1027.
-
(2009)
, pp. 1022-1027
-
-
Wang, F.1
Sun, J.2
Li, T.3
Anerousis, N.4
-
29
-
-
85196063193
-
-
Spectral relaxation for k-means clustering, In Advances in Neural Information Processing Systems
-
H. Zha, X. He, C. Ding, H. Simon, and M. Gu, Spectral relaxation for k-means clustering, In Advances in Neural Information Processing Systems, 2001, 1057-1064.
-
(2001)
, pp. 1057-1064
-
-
Zha, H.1
He, X.2
Ding, C.3
Simon, H.4
Gu, M.5
-
30
-
-
0004094721
-
-
Cambridge, MA, MIT press
-
B. Schölkopf and A. J. Smola, Learning with Kernels: Support Vector Machines, Regularization, Optimization, and Beyond, Cambridge, MA, MIT press, 2002.
-
(2002)
Learning with Kernels: Support Vector Machines, Regularization, Optimization, and Beyond
-
-
Schölkopf, B.1
Smola, A.J.2
-
31
-
-
84942484786
-
Ridge regression: biased estimation for nonorthogonal problems
-
A. E. Hoerl and R. Kennard, Ridge regression: biased estimation for nonorthogonal problems, Technometrics 12 (1970), 55-67.
-
(1970)
Technometrics
, vol.12
, pp. 55-67
-
-
Hoerl, A.E.1
Kennard, R.2
-
32
-
-
56449092085
-
-
Efficient projections onto the l1-ball for learning in high dimensions, In Proceedings of the 25th international conference on Machine learning
-
J. Duchi, S. Shalev-Shwartz, Y. Singer, and T. Chandra, Efficient projections onto the l1-ball for learning in high dimensions, In Proceedings of the 25th international conference on Machine learning, 2008. 272-279.
-
(2008)
, pp. 272-279
-
-
Duchi, J.1
Shalev-Shwartz, S.2
Singer, Y.3
Chandra, T.4
-
33
-
-
85196122339
-
-
Efficient euclidean projections in linear time, In Proceedings of the 26th international conference on Machine learning.
-
J. Liu and J. Ye, Efficient euclidean projections in linear time, In Proceedings of the 26th international conference on Machine learning.
-
-
-
Liu, J.1
Ye, J.2
-
34
-
-
0001287271
-
Regression shrinkage and selection via the lasso
-
1) ()
-
R. Tibshirani, Regression shrinkage and selection via the lasso, J R Stat Soc [Ser B] 58 (1) (1996), 267-288.
-
(1996)
J R Stat Soc [Ser B]
, vol.58
, pp. 267-288
-
-
Tibshirani, R.1
-
35
-
-
3242708140
-
Least angle regression
-
2) ()
-
B. Efron, T. Hastie, I. Johnstone, and R. Tibshirani, Least angle regression, Ann Stat 32(2) (2004), 407-499.
-
(2004)
Ann Stat
, vol.32
, pp. 407-499
-
-
Efron, B.1
Hastie, T.2
Johnstone, I.3
Tibshirani, R.4
-
36
-
-
16244401458
-
Regularization and variable selection via the elastic net
-
2) ()
-
H. Zou and T. Trevor, Regularization and variable selection via the elastic net, J R Stat Soc [Ser B] 67(2) (2005), 301-320.
-
(2005)
J R Stat Soc [Ser B]
, vol.67
, pp. 301-320
-
-
Zou, H.1
Trevor, T.2
-
37
-
-
51749101269
-
-
Approximate l0 constrained non-negative matrix and tensor factorization, In Proceedings of IEEE International Symposium on Circuits and Systems
-
M. Morup, K. H. Madsen, and L. K. Hansen, Approximate l0 constrained non-negative matrix and tensor factorization, In Proceedings of IEEE International Symposium on Circuits and Systems, 2008, 1328-1331.
-
(2008)
, pp. 1328-1331
-
-
Morup, M.1
Madsen, K.H.2
Hansen, L.K.3
-
38
-
-
0004236492
-
-
3rd ed.), Baltimore, MD, The Johns Hopkins University Press
-
G. H. Golub and C. F. V. Loan, Matrix Computation (3rd ed.), Baltimore, MD, The Johns Hopkins University Press, 1996.
-
(1996)
Matrix Computation
-
-
Golub, G.H.1
Loan, C.F.V.2
-
39
-
-
33646023117
-
An introduction to roc analysis
-
T. Fawcett, An introduction to roc analysis, Pattern Recognit Lett 27 (2006), 861-874.
-
(2006)
Pattern Recognit Lett
, vol.27
, pp. 861-874
-
-
Fawcett, T.1
-
40
-
-
69549133517
-
Measuring classifier performance: a coherent alternative to the area under the roc curve
-
D. J. HMeasuring classifier performance: a coherent alternative to the area under the roc curve, Mach Learn 77 (2009), 103-123.
-
(2009)
Mach Learn
, vol.77
, pp. 103-123
-
-
Hand, D.J.1
|