-
2
-
-
0036583160
-
A parallel mixture of SVMs for very large scale problems
-
May
-
R. Collobert, S. Bengio, and Y. Bengio, "A parallel mixture of SVMs for very large scale problems," Neural Comput., vol. 14, no. 5, pp. 1105-1114, May 2002.
-
(2002)
Neural Comput
, vol.14
, Issue.5
, pp. 1105-1114
-
-
Collobert, R.1
Bengio, S.2
Bengio, Y.3
-
3
-
-
84899010839
-
-
C. Williams and M. Seeger, T. Leen, T. Dietterich, and V. Tresp, Eds., Using the Nyström method to speed up kernel machines, in Advances in Neural Information Processing Systems. Cambridge, MA: MIT Press, 2001, 13, pp. 682-688.
-
C. Williams and M. Seeger, , T. Leen, T. Dietterich, and V. Tresp, Eds., "Using the Nyström method to speed up kernel machines," in Advances in Neural Information Processing Systems. Cambridge, MA: MIT Press, 2001, vol. 13, pp. 682-688.
-
-
-
-
4
-
-
0002493574
-
Sparse greedy matrix approximation for machine learning
-
Stanford, CA, Jun
-
A. Smola and B. Schölkopf, "Sparse greedy matrix approximation for machine learning," in Proc. 7th Int. Conf. Mach. Learn., Stanford, CA, Jun. 2000, pp. 911-918.
-
(2000)
Proc. 7th Int. Conf. Mach. Learn
, pp. 911-918
-
-
Smola, A.1
Schölkopf, B.2
-
5
-
-
84898967665
-
Sampling techniques for kernel methods
-
T. Dietterich, S. Becker, and Z. Ghahramani, Eds. Cambridge, MA: MIT Press
-
D. Achlioptas, F. McSherry, and B. Schölkopf, "Sampling techniques for kernel methods," in Advances in Neural Information Processing Systems, T. Dietterich, S. Becker, and Z. Ghahramani, Eds. Cambridge, MA: MIT Press, 2002, vol. 14, pp. 335-342.
-
(2002)
Advances in Neural Information Processing Systems
, vol.14
, pp. 335-342
-
-
Achlioptas, D.1
McSherry, F.2
Schölkopf, B.3
-
6
-
-
0041494125
-
Efficient SVM training using low-rank kernel representations
-
Dec
-
S. Fine and K. Scheinberg, "Efficient SVM training using low-rank kernel representations," J. Mach. Learn. Res., vol. 2, pp. 243-264, Dec. 2001.
-
(2001)
J. Mach. Learn. Res
, vol.2
, pp. 243-264
-
-
Fine, S.1
Scheinberg, K.2
-
9
-
-
0030673582
-
Training support vector machines: An application to face detection
-
San Juan, PR, Jun
-
E. Osuna, R. Freund, and F. Girosi, "Training support vector machines: An application to face detection," in Proc. Conf. Comput. Vis. Pattern Recognit., San Juan, PR, Jun. 1997, pp. 130-136.
-
(1997)
Proc. Conf. Comput. Vis. Pattern Recognit
, pp. 130-136
-
-
Osuna, E.1
Freund, R.2
Girosi, F.3
-
10
-
-
0003120218
-
Fast training of support vector machines using sequential minimal optimization
-
J. Platt, B. Schölkopf, C. Burges, and A. Smola, Eds, Cambridge, MA: MIT Press
-
J. Platt, , B. Schölkopf, C. Burges, and A. Smola, Eds., "Fast training of support vector machines using sequential minimal optimization," in Advances in Kernel Methods - Support Vector Learning. Cambridge, MA: MIT Press, 1999, pp. 185-208.
-
(1999)
Advances in Kernel Methods - Support Vector Learning
, pp. 185-208
-
-
-
11
-
-
1942516515
-
SimpleSVM
-
Washington, D.C, Aug
-
S. Vishwanathan, A. Smola, and M. Murty, "SimpleSVM," in Proc. 20th Int. Conf. Mach. Learn., Washington, D.C., Aug. 2003, pp. 760-767.
-
(2003)
Proc. 20th Int. Conf. Mach. Learn
, pp. 760-767
-
-
Vishwanathan, S.1
Smola, A.2
Murty, M.3
-
12
-
-
19344375172
-
Rigorous proof of termination of SMO algorithm for support vector machines
-
May
-
N. Takahashi and T. Nishi, "Rigorous proof of termination of SMO algorithm for support vector machines," IEEE Trans. Neural Netw., vol. 16, no. 3, pp. 774-776, May 2005.
-
(2005)
IEEE Trans. Neural Netw
, vol.16
, Issue.3
, pp. 774-776
-
-
Takahashi, N.1
Nishi, T.2
-
13
-
-
34147093886
-
Scaling-up support vector machines using boosting algorithm
-
Barcelona, Spain, Sep
-
D. Pavlov, J. Mao, and B. Dom, "Scaling-up support vector machines using boosting algorithm," in Proc. Int. Conf. Pattern Recognit., Barcelona, Spain, Sep. 2000, vol. 2, pp. 2219-2222.
-
(2000)
Proc. Int. Conf. Pattern Recognit
, vol.2
, pp. 2219-2222
-
-
Pavlov, D.1
Mao, J.2
Dom, B.3
-
14
-
-
0041414854
-
RSVM: Reduced support vector machines
-
San Jose, CA
-
Y.-J. Lee and O. Mangasarian, "RSVM: Reduced support vector machines," in Proc. 1st SIAM Int. Conf. Data Mining, San Jose, CA, 2001, pp. 184-200.
-
(2001)
Proc. 1st SIAM Int. Conf. Data Mining
, pp. 184-200
-
-
Lee, Y.-J.1
Mangasarian, O.2
-
15
-
-
0000897328
-
The Kernel-Adatron algorithm: A fast and simple learning procedure for support vector machines
-
Madison, WI, Jul
-
T. Friess, N. Cristianini, and C. Campbell, "The Kernel-Adatron algorithm: A fast and simple learning procedure for support vector machines," in Proc. 15th Int. Conf. Mach. Learn., Madison, WI, Jul. 1998, pp. 188-196.
-
(1998)
Proc. 15th Int. Conf. Mach. Learn
, pp. 188-196
-
-
Friess, T.1
Cristianini, N.2
Campbell, C.3
-
16
-
-
15344351150
-
An improved conjugate gradient scheme to the solution of least squares SVM
-
Mar
-
W. Chu, C. Ong, and S. Keerthi, "An improved conjugate gradient scheme to the solution of least squares SVM," IEEE Trans. Neural Netw., vol. 16, no. 2, pp. 498-501, Mar. 2005.
-
(2005)
IEEE Trans. Neural Netw
, vol.16
, Issue.2
, pp. 498-501
-
-
Chu, W.1
Ong, C.2
Keerthi, S.3
-
17
-
-
23044525572
-
Scaling kernel-based systems to large data sets
-
V. Tresp, "Scaling kernel-based systems to large data sets," Data Mining Knowl. Discovery, vol. 5, no. 3, pp. 197-211, 2001.
-
(2001)
Data Mining Knowl. Discovery
, vol.5
, Issue.3
, pp. 197-211
-
-
Tresp, V.1
-
18
-
-
21844440579
-
Core vector machines: Fast SVM training on very large data sets
-
I. W. Tsang, J. T. Kwok, and P.-M. Cheung, "Core vector machines: Fast SVM training on very large data sets," J. Mach. Learn. Res., vol. 6, pp. 363-392, 2005.
-
(2005)
J. Mach. Learn. Res
, vol.6
, pp. 363-392
-
-
Tsang, I.W.1
Kwok, J.T.2
Cheung, P.-M.3
-
19
-
-
0000487102
-
Estimating the support of a high-dimensional distribution
-
Jul
-
B. Schölkopf, J. Platt, J. Shawe-Taylor, A. Smola, and R. Williamson, "Estimating the support of a high-dimensional distribution," Neural Comput., vol. 13, no. 7, pp. 1443-1471, Jul. 2001.
-
(2001)
Neural Comput
, vol.13
, Issue.7
, pp. 1443-1471
-
-
Schölkopf, B.1
Platt, J.2
Shawe-Taylor, J.3
Smola, A.4
Williamson, R.5
-
20
-
-
0242456822
-
Optimizing search engines using clickthrough data
-
Edmonton, AB, Canada
-
T. Joachims, "Optimizing search engines using clickthrough data," in Proc. 8th ACM SIGKDD Int. Conf. Knowl. Discovery and Data Mining, Edmonton, AB, Canada, 2002, pp. 133-142.
-
(2002)
Proc. 8th ACM SIGKDD Int. Conf. Knowl. Discovery and Data Mining
, pp. 133-142
-
-
Joachims, T.1
-
21
-
-
4043137356
-
A tutorial on support vector regression
-
Aug
-
A. Smola and B. Schölkopf, "A tutorial on support vector regression," Stat. Comput., vol. 14, no. 3, pp. 199-222, Aug. 2004.
-
(2004)
Stat. Comput
, vol.14
, Issue.3
, pp. 199-222
-
-
Smola, A.1
Schölkopf, B.2
-
22
-
-
31844443910
-
Core vector regression for very large regression problems
-
Bonn, Germany, Aug
-
I. W. Tsang, J. T. Kwok, and K. T. Lai, "Core vector regression for very large regression problems," in Proc. 22nd Int. Conf. Mach. Learn., Bonn, Germany, Aug. 2005, pp. 913-920.
-
(2005)
Proc. 22nd Int. Conf. Mach. Learn
, pp. 913-920
-
-
Tsang, I.W.1
Kwok, J.T.2
Lai, K.T.3
-
23
-
-
33947417485
-
Very large SVM training using core vector machines
-
Barbados, Jan
-
I. Tsang, J. Kwok, and P.-M. Cheung, "Very large SVM training using core vector machines," in Proc. 10th Int. Workshop Artif. Intell. Stat., Barbados, Jan. 2005, pp. 349-356.
-
(2005)
Proc. 10th Int. Workshop Artif. Intell. Stat
, pp. 349-356
-
-
Tsang, I.1
Kwok, J.2
Cheung, P.-M.3
-
25
-
-
33244496848
-
Geometric approximation via coresets
-
P. Agarwal, S. Har-Peled, and K. Varadarajan, E. Welzl, Ed, Cambridge, U.K, Cambridge Univ. Press
-
P. Agarwal, S. Har-Peled, and K. Varadarajan, , E. Welzl, Ed., "Geometric approximation via coresets," in Current Trends in Combinatorial and Computational Geometry. Cambridge, U.K.: Cambridge Univ. Press, 2005.
-
(2005)
Current Trends in Combinatorial and Computational Geometry
-
-
-
26
-
-
21844454075
-
Optimal core-sets for balls
-
presented at the, Piscataway, NJ, Nov
-
M. Bädoiu and K. Clarkson, "Optimal core-sets for balls," presented at the DIMACS Workshop Comput. Geometry, Piscataway, NJ, Nov. 2002.
-
(2002)
DIMACS Workshop Comput. Geometry
-
-
Bädoiu, M.1
Clarkson, K.2
-
27
-
-
0033220728
-
Support vector domain description
-
D. Tax and R. Duin, "Support vector domain description," Pattern Recognit. Lett., vol. 20, no. 14, pp. 1191-1199, 1999.
-
(1999)
Pattern Recognit. Lett
, vol.20
, Issue.14
, pp. 1191-1199
-
-
Tax, D.1
Duin, R.2
-
28
-
-
2342636412
-
Shape fitting with outliers
-
S. Har-Peled and Y. Wang, "Shape fitting with outliers," SIAM J. Comput., vol. 33, no. 2, pp. 269-285, 2004.
-
(2004)
SIAM J. Comput
, vol.33
, Issue.2
, pp. 269-285
-
-
Har-Peled, S.1
Wang, Y.2
-
29
-
-
0347512512
-
Lagrangian support vector machines
-
O. Mangasarian and D. Musicant, "Lagrangian support vector machines," J. Mach. Learn. Res., vol. 1, pp. 161-177, 2001.
-
(2001)
J. Mach. Learn. Res
, vol.1
, pp. 161-177
-
-
Mangasarian, O.1
Musicant, D.2
-
30
-
-
0002714543
-
Making large-scale support vector machine learning practical
-
T. Joachims, B. Schölkopf, C. Burges, and A. Smola, Eds, Cambridge, MA: MIT Press
-
T. Joachims, B. Schölkopf, C. Burges, and A. Smola, Eds., "Making large-scale support vector machine learning practical," in Advances in Kernel Methods - Support Vector Learning. Cambridge, MA: MIT Press, 1999, pp. 169-184.
-
(1999)
Advances in Kernel Methods - Support Vector Learning
, pp. 169-184
-
-
-
31
-
-
2442593945
-
Active set support vector regression
-
Mar
-
D. Musicant and A. Feinberg, "Active set support vector regression," IEEE Trans. Neural Netw., vol. 15, no. 2, pp. 268-275, Mar. 2004.
-
(2004)
IEEE Trans. Neural Netw
, vol.15
, Issue.2
, pp. 268-275
-
-
Musicant, D.1
Feinberg, A.2
-
32
-
-
0002432565
-
Multivariate adaptive regression splines (with discussion)
-
J. Friedman, "Multivariate adaptive regression splines (with discussion)," Ann. Stat.,vol. 19, no. 1, pp. 1-141, 1991.
-
(1991)
Ann. Stat
, vol.19
, Issue.1
, pp. 1-141
-
-
Friedman, J.1
-
33
-
-
33947392369
-
-
K.-K. Sung, Learning and Example Selection for Object and Pattern Recognition, Ph.D. dissertation, Artif. Intell. Lab. and Cntr. Biol. Comput. Learn., MIT, Cambridge, MA, 1996.
-
K.-K. Sung, "Learning and Example Selection for Object and Pattern Recognition," Ph.D. dissertation, Artif. Intell. Lab. and Cntr. Biol. Comput. Learn., MIT, Cambridge, MA, 1996.
-
-
-
-
34
-
-
21844457797
-
Dealing with large diagonals in kernel matrices
-
Principles of Data Mining and Knowledge Discovery. Helsinki, Finland: Springer-Verlag
-
J. Weston, B. Schölkopf, E. Eskin, C. Leslie, and S. Noble, "Dealing with large diagonals in kernel matrices," in Principles of Data Mining and Knowledge Discovery. Helsinki, Finland: Springer-Verlag, 2002, vol. 243, Lecture Notes in Computer Science, pp. 494-511.
-
(2002)
Lecture Notes in Computer Science
, vol.243
, pp. 494-511
-
-
Weston, J.1
Schölkopf, B.2
Eskin, E.3
Leslie, C.4
Noble, S.5
-
35
-
-
0031191630
-
The use of the area under the ROC curve in the evaluation of machine learning algorithms
-
A. Bradley, "The use of the area under the ROC curve in the evaluation of machine learning algorithms," Pattern Recognit., vol. 30, no. 7, pp. 1145-1159, 1997.
-
(1997)
Pattern Recognit
, vol.30
, Issue.7
, pp. 1145-1159
-
-
Bradley, A.1
-
37
-
-
31844439279
-
Large scale genomic sequence SVM classifiers
-
Bonn, Germany, Aug
-
S. Sonnenburg, G. Rätsch, and B. Schölkopf, "Large scale genomic sequence SVM classifiers," in Proc. 22nd Int. Conf. Mach. Learn., Bonn, Germany, Aug. 2005, pp. 849-856.
-
(2005)
Proc. 22nd Int. Conf. Mach. Learn
, pp. 849-856
-
-
Sonnenburg, S.1
Rätsch, G.2
Schölkopf, B.3
-
38
-
-
72849123507
-
-
P. Kumar, J. Mitchell, and A. Yildirim, Approximate minimum enclosing balls in high dimensions using core-sets, ACM J. Exp. Algorithmics, 8, p. 1.1, Jan. 2003.
-
P. Kumar, J. Mitchell, and A. Yildirim, "Approximate minimum enclosing balls in high dimensions using core-sets," ACM J. Exp. Algorithmics, vol. 8, p. 1.1, Jan. 2003.
-
-
-
|