-
1
-
-
79952749920
-
Variable sparsity kernel learning
-
Aflalo, J., Ben-Tal, A., Bhattacharyya, C., Nath, J. Saketha, and Raman, S. Variable sparsity kernel learning. JMLR, 12:565- 592, 2011.
-
(2011)
JMLR
, vol.12
, pp. 565-592
-
-
Aflalo, J.1
Ben-Tal, A.2
Bhattacharyya, C.3
Nath, J.S.4
Raman, S.5
-
2
-
-
84971957489
-
Continuation and path following
-
Allgower, E. L. and Georg, K. Continuation and path following. Acta Numer, 2:1-64, 1993.
-
(1993)
Acta Numer
, vol.2
, pp. 1-64
-
-
Allgower, E.L.1
Georg, K.2
-
3
-
-
34547984768
-
Scalable training of L-l-regularized log- linear models
-
Andrew, G. and Gao, J. Scalable training of L-l-regularized log- linear models. In ICML, pp. 33-40, 2007.
-
(2007)
ICML
, pp. 33-40
-
-
Andrew, G.1
Gao, J.2
-
4
-
-
84858766876
-
Exploring large feature spaces with hierarchical multiple kernel learning
-
Bach, F. R. Exploring large feature spaces with hierarchical multiple kernel learning. In NIPS, pp. 105-112, 2008.
-
(2008)
NIPS
, pp. 105-112
-
-
Bach, F.R.1
-
5
-
-
23244435214
-
Computing regularization paths for learning multiple kernels
-
Bach, F. R., Thibaux, R., and Jordan, M. I. Computing regularization paths for learning multiple kernels. In NIPS, 2004.
-
(2004)
NIPS
-
-
Bach, F.R.1
Thibaux, R.2
Jordan, M.I.3
-
6
-
-
33748436837
-
Boosting sex identification performance
-
Baluja, S. and Rowley, H. Boosting sex identification performance. IJCV, 71(1):111-119, 2007.
-
(2007)
IJCV
, vol.71
, Issue.1
, pp. 111-119
-
-
Baluja, S.1
Rowley, H.2
-
7
-
-
26244461684
-
Clustering with bregman divergences
-
Baneijee, A., Merugu, S., Dhillon, I. S., and Ghosh, J. Clustering with bregman divergences. JMLR, 6:1705-1749, 2005.
-
(2005)
JMLR
, vol.6
, pp. 1705-1749
-
-
Baneijee, A.1
Merugu, S.2
Dhillon, I.S.3
Ghosh, J.4
-
8
-
-
0347242385
-
Lectures on modern convex optimization: Analysis, algorithms and engineering applications
-
Ben-Tal, A. and Nemirovski, A. Lectures on Modern Convex Optimization: Analysis, Algorithms and Engineering Applications. MPS/SIAM Series on Optimization, 1, 2001.
-
(2001)
MPS/SIAM Series on Optimization
, pp. 1
-
-
Ben-Tal, A.1
Nemirovski, A.2
-
9
-
-
0038368335
-
Stability and generalization
-
Bousquet, O. and Elisseeff, A. Stability and generalization. JMLR, 2:499-526, 2002.
-
(2002)
JMLR
, vol.2
, pp. 499-526
-
-
Bousquet, O.1
Elisseeff, A.2
-
10
-
-
71749097475
-
Feature selection in a kernel space
-
Cao, B., Shen, D., Sun, J. T., Yang, Q., and Chen, Z. Feature selection in a kernel space. In ICML, 2007.
-
(2007)
ICML
-
-
Cao, B.1
Shen, D.2
Sun, J.T.3
Yang, Q.4
Chen, Z.5
-
11
-
-
34547971383
-
Direct convex relaxations of sparse SVM
-
Chan, A. B., Vasconcelos, N., and Lanckriet, G. Direct convex relaxations of sparse SVM. In ICML, pp. 145-153, 2007.
-
(2007)
ICML
, pp. 145-153
-
-
Chan, A.B.1
Vasconcelos, N.2
Lanckriet, G.3
-
12
-
-
65449122452
-
Learning subspace kernels for classification
-
Chen, J., Ji, S., Ceran, B., Li, Q., Wu, M., and Ye, J. Learning subspace kernels for classification. In KDD, 2008.
-
(2008)
KDD
-
-
Chen, J.1
Ji, S.2
Ceran, B.3
Li, Q.4
Wu, M.5
Ye, J.6
-
14
-
-
84858743760
-
Learning non-linear combinations of kernels
-
Cortes, C., Mohri, M., and Rostamizadeh, A. Learning non-linear combinations of kernels. In NIPS, 2009b.
-
(2009)
NIPS
-
-
Cortes, C.1
Mohri, M.2
Rostamizadeh, A.3
-
15
-
-
84859463794
-
Algorithms for learning kernels based on centered alignment
-
Cortes, C., Mohri, M., and Rostamizadeh, A. Algorithms for learning kernels based on centered alignment. JMLR, 13:795- 828, 2012.
-
(2012)
JMLR
, vol.13
, pp. 795-828
-
-
Cortes, C.1
Mohri, M.2
Rostamizadeh, A.3
-
17
-
-
0041995195
-
On kernel-target alignment
-
Cristianini, N., Shawe-Taylor, J., Elisseeff, A., and Kandola, J. On kernel-target alignment. In NIPS, 2001.
-
(2001)
NIPS
-
-
Cristianini, N.1
Shawe-Taylor, J.2
Elisseeff, A.3
Kandola, J.4
-
19
-
-
85156255820
-
Adaptive scaling for feature selection in svms
-
Grandvalet, Y. and Canu, S. Adaptive scaling for feature selection in svms. In NIPS, 2002.
-
(2002)
NIPS
-
-
Grandvalet, Y.1
Canu, S.2
-
20
-
-
76649126602
-
Computing the solution path for the regularized support vector regression
-
Gunter, L. and Zhu, J. Computing the solution path for the regularized support vector regression. In NIPS, 2005.
-
(2005)
NIPS
-
-
Gunter, L.1
Zhu, J.2
-
21
-
-
33745891586
-
-
Springer-Verlag New York, Inc
-
Guyon, I., Gunn, S., Nikravesh, M., and Zadeh, L. A. Feature Extraction: Foundations and Applications. Springer-Verlag New York, Inc., 2006.
-
(2006)
Feature Extraction: Foundations and Applications
-
-
Guyon, I.1
Gunn, S.2
Nikravesh, M.3
Zadeh, L.A.4
-
22
-
-
84925605946
-
The entire regularization path for the support vector machine
-
Hastie, T., Rosset, S., Tibshirani, R., and Zhu, J. The entire regularization path for the support vector machine. JMLR, 5:1391- 1415, 2004.
-
(2004)
JMLR
, vol.5
, pp. 1391-1415
-
-
Hastie, T.1
Rosset, S.2
Tibshirani, R.3
Zhu, J.4
-
23
-
-
80052908079
-
Sharing features between objects and their attributes
-
Hwang, S. J., Sha, F., and Grauman, K. Sharing features between objects and their attributes. In CVPR, pp. 1761-1768, 2011.
-
(2011)
CVPR
, pp. 1761-1768
-
-
Hwang, S.J.1
Sha, F.2
Grauman, K.3
-
24
-
-
84877777363
-
Semantic kernel forests from multiple taxonomies
-
Hwang, S. J., Grauman, K., and Sha, F. Semantic kernel forests from multiple taxonomies. In NIPS, 2012.
-
(2012)
NIPS
-
-
Hwang, S.J.1
Grauman, K.2
Sha, F.3
-
25
-
-
84866010566
-
Spg-gmkl: Generalized multiple kernel learning with a million kernels
-
Jain, A., Vishwanathan, S. V. N., and Varma, M. Spg-gmkl: Generalized multiple kernel learning with a million kernels. In KDD, 2012.
-
(2012)
KDD
-
-
Jain, A.1
Vishwanathan, S.V.N.2
Varma, M.3
-
26
-
-
70350627315
-
Multi-label multiple kernel learning
-
Ji, S., Sun, L., Jin, R., and Ye, J. Multi-label multiple kernel learning. In NIPS, 2008.
-
(2008)
NIPS
-
-
Ji, S.1
Sun, L.2
Jin, R.3
Ye, J.4
-
27
-
-
33646032356
-
The p-norm generaliziation of the LMS algorithm for adaptive filtering
-
Kivinen, J., Warmuth, M. K., and Hassibi, B. The p-norm generaliziation of the LMS algorithm for adaptive filtering. IEEE Trans. Signal Processing, 54(5): 1782-1793, 2006.
-
(2006)
IEEE Trans. Signal Processing
, vol.54
, Issue.5
, pp. 1782-1793
-
-
Kivinen, J.1
Warmuth, M.K.2
Hassibi, B.3
-
28
-
-
79955848223
-
Lp-norm multiple kernel learning
-
Kloft, M., Brefeld, U., Sonnenburg, S., and Zien, A. lp-norm multiple kernel learning. JMLR, 12:953-997, 2011.
-
(2011)
JMLR
, vol.12
, pp. 953-997
-
-
Kloft, M.1
Brefeld, U.2
Sonnenburg, S.3
Zien, A.4
-
29
-
-
8844278523
-
Learning the kernel matrix with semidefinite programming
-
Lanckriet, G. R. G., Cristianini, N., Bartlett, P., El Ghaoui, L., and Jordan, M. I. Learning the kernel matrix with semidefinite programming. JMLR, 5:27-72, 2004.
-
(2004)
JMLR
, vol.5
, pp. 27-72
-
-
Lanckriet, G.R.G.1
Cristianini, N.2
Bartlett, P.3
El Ghaoui, L.4
Jordan, M.I.5
-
30
-
-
84919888893
-
Learning the kernel matrix with low- rank multiplicative shaping
-
Levinboim, T. and Sha, F. Learning the kernel matrix with low- rank multiplicative shaping. In AAAI, 2012.
-
(2012)
AAAI
-
-
Levinboim, T.1
Sha, F.2
-
31
-
-
84867872920
-
The feature selection path in kernel methods
-
Li, F. and Sminchisescu, C. The feature selection path in kernel methods. In AISTATS, 2010.
-
(2010)
AISTATS
-
-
Li, F.1
Sminchisescu, C.2
-
32
-
-
84919888892
-
From lasso regression to feature vector machine
-
Li, F., Yang, Y., and Xing, E. From lasso regression to feature vector machine. In NIPS, 2006.
-
(2006)
NIPS
-
-
Li, F.1
Yang, Y.2
Xing, E.3
-
33
-
-
80053459750
-
Ultra-fast optimization algorithm for sparse multi kernel learning
-
Orabona, F. and Jie, L. Ultra-fast optimization algorithm for sparse multi kernel learning. In ICML, 2011.
-
(2011)
ICML
-
-
Orabona, F.1
Jie, L.2
-
34
-
-
84857883067
-
Multi kernel learning with online-batch optimization
-
Orabona, F., Luo, J., and Caputo, B. Multi kernel learning with online-batch optimization. JMLR, 13:227-253, 2012.
-
(2012)
JMLR
, vol.13
, pp. 227-253
-
-
Orabona, F.1
Luo, J.2
Caputo, B.3
-
35
-
-
57249084590
-
Sim- pleMKL
-
Rakotomamonjy, A., Bach, F., Grandvalet, Y., and Canu, S. Sim- pleMKL. JMLR, 9:2491-2521, 2008.
-
(2008)
JMLR
, vol.9
, pp. 2491-2521
-
-
Rakotomamonjy, A.1
Bach, F.2
Grandvalet, Y.3
Canu, S.4
-
36
-
-
33745784116
-
Following curved regularized optimization solution paths
-
Rosset, S. Following curved regularized optimization solution paths. In NIPS, 2004.
-
(2004)
NIPS
-
-
Rosset, S.1
-
37
-
-
84862024860
-
Feature selection via dependence maximization
-
Song, L., Smola, A., Gretton, A., Bedo, J., and Borgwardt, K. Feature selection via dependence maximization. JMLR, 13: 1393-1434, 2012.
-
(2012)
JMLR
, vol.13
, pp. 1393-1434
-
-
Song, L.1
Smola, A.2
Gretton, A.3
Bedo, J.4
Borgwardt, K.5
-
38
-
-
71149100224
-
More generality in efficient multiple kernel learning
-
Varma, M. and Babu, B. R. More generality in efficient multiple kernel learning. In ICML, 2009.
-
(2009)
ICML
-
-
Varma, M.1
Babu, B.R.2
-
39
-
-
77953196456
-
Multiple kernels for object detection
-
Vedaldi, A., Gulshan, V., Varma, M., and Zisserman, A. Multiple kernels for object detection. In ICCV, 2009.
-
(2009)
ICCV
-
-
Vedaldi, A.1
Gulshan, V.2
Varma, M.3
Zisserman, A.4
-
40
-
-
85162016686
-
Multiple kernel learning and the smo algorithm
-
Vishwanathan, S. V. N., Sun, Z., Theera-Ampornpunt, N., and Varma, M. Multiple kernel learning and the smo algorithm. In NIPS, 2010.
-
(2010)
NIPS
-
-
Vishwanathan, S.V.N.1
Sun, Z.2
Theera-Ampornpunt, N.3
Varma, M.4
-
41
-
-
33749253889
-
Two-dimensional solution path for support vector regression
-
Wang, G., Yeung, D.-Y., and Lochovsky, F. H. Two-dimensional solution path for support vector regression. In ICML, 2006.
-
(2006)
ICML
-
-
Wang, G.1
Yeung, D.-Y.2
Lochovsky, F.H.3
-
42
-
-
84862276865
-
A kernel path algorithm for support vector machines
-
Wang, G., Yeung, D.-Y., and Lochovsky, F. H. A kernel path algorithm for support vector machines. In ICML, 2007.
-
(2007)
ICML
-
-
Wang, G.1
Yeung, D.-Y.2
Lochovsky, F.H.3
-
43
-
-
0001001098
-
Feature selection for svms
-
Weston, J., Mukherjee, S., Chapelle, O., Pontil, M., Poggio, T., and Vapnik, V. Feature selection for svms. In NIPS, 2000.
-
(2000)
NIPS
-
-
Weston, J.1
Mukherjee, S.2
Chapelle, O.3
Pontil, M.4
Poggio, T.5
Vapnik, V.6
-
44
-
-
31844432832
-
Building sparse large margin classifier
-
Wu, M., Scholkopf, B., and Bakir, G. Building sparse large margin classifier. In ICML, 2005.
-
(2005)
ICML
-
-
Wu, M.1
Scholkopf, B.2
Bakir, G.3
-
45
-
-
44649123652
-
Multi-class discriminant kernel learning via convex programming
-
Ye, J.,, Ji, S., and Chen, J. Multi-class discriminant kernel learning via convex programming. JMLR, 9:719-758, 2008.
-
(2008)
JMLR
, vol.9
, pp. 719-758
-
-
Ye, J.1
Ji, S.2
Chen, J.3
-
46
-
-
37749006178
-
Stagewise lasso
-
Zhao, P. and Yu, B. Stagewise lasso. JMLR, 8:2701-2726, 2007.
-
(2007)
JMLR
, vol.8
, pp. 2701-2726
-
-
Zhao, P.1
Yu, B.2
-
47
-
-
79957625130
-
Advancing feature selection research
-
Zhao, Z., Morstatter, F., Sharma, S., Alelyani, S., Anand, A., and Liu, H. Advancing feature selection research. Technical report, Arizona State University, 2010.
-
(2010)
Technical Report, Arizona State University
-
-
Zhao, Z.1
Morstatter, F.2
Sharma, S.3
Alelyani, S.4
Anand, A.5
Liu, H.6
-
48
-
-
24644515558
-
1-norm support vector machines
-
Zhu, J., Rosset, S., Hastie, T., and Tibshirani, R. 1-norm Support Vector Machines. In NIPS, 2003.
-
(2003)
NIPS
-
-
Zhu, J.1
Rosset, S.2
Hastie, T.3
Tibshirani, R.4
-
49
-
-
16244401458
-
Regularization and variable seclection via the elastic net
-
Zou, H. and Hastie, T. Regularization and variable seclection via the elastic net. Journal of the Royal Statistical Society B, 67 (2):301-320, 2005.
-
(2005)
Journal of the Royal Statistical Society B
, vol.67
, Issue.2
, pp. 301-320
-
-
Zou, H.1
Hastie, T.2
|