-
1
-
-
0002429764
-
A column generation algorithm for boosting
-
P. Langley, editor, San Francisco, Morgan Kaufmann Publishers
-
K. P. Bennett, A. Demiriz, and J. Shawe-Taylor. A column generation algorithm for boosting. In P. Langley, editor, Proceedings of the International Conference on Machine Learning, San Francisco, 2000. Morgan Kaufmann Publishers.
-
(2000)
Proceedings of the International Conference on Machine Learning
-
-
Bennett, K.P.1
Demiriz, A.2
Shawe-Taylor, J.3
-
2
-
-
0026860799
-
Robust linear programming discrimination of two linearly inseparable sets
-
K. P. Bennett and O. L. Mangasarian. Robust linear programming discrimination of two linearly inseparable sets. Optimization Methods and Software, 1:23-34, 1992.
-
(1992)
Optimization Methods and Software
, vol.1
, pp. 23-34
-
-
Bennett, K.P.1
Mangasarian, O.L.2
-
5
-
-
0002709342
-
Feature selection via concave minimization and support vector machines
-
J. Shavlik, editor, San Francisco, California, Morgan Kaufmann Publishers
-
P. S. Bradley and O. L. Mangasarian. Feature selection via concave minimization and support vector machines. In J. Shavlik, editor, Proceedings of the International Conference on Machine Learning, pages 82-90, San Francisco, California, 1998. Morgan Kaufmann Publishers, ftp://ftp.cs.wisc.edu/math-prog/tech-reports/98-03.ps.Z.
-
(1998)
Proceedings of the International Conference on Machine Learning
, pp. 82-90
-
-
Bradley, P.S.1
Mangasarian, O.L.2
-
6
-
-
0032131292
-
Atomic decomposition by basis pursuit
-
S. Chen, D. Donoho, and M. Saunders. Atomic decomposition by basis pursuit. Siam Journal of Scientific Computing, 20(1):33-61, 1999.
-
(1999)
Siam Journal of Scientific Computing
, vol.20
, Issue.1
, pp. 33-61
-
-
Chen, S.1
Donoho, D.2
Saunders, M.3
-
9
-
-
84898947911
-
Sparse representation for Gaussian process models
-
T. K. Leen, T. G. Dietterich, and V. Tresp, editors, MIT Press
-
L. Csató and M. Opper. Sparse representation for Gaussian process models. In T. K. Leen, T. G. Dietterich, and V. Tresp, editors, Advances in Neural Information Processing Systems 13, pages 444-450. MIT Press, 2001.
-
(2001)
Advances in Neural Information Processing Systems 13
, pp. 444-450
-
-
Csató, L.1
Opper, M.2
-
10
-
-
0002629270
-
Maximum Likelihood from Incomplete Data via the EM Algorithm
-
A. P. Dempster, N. M. Laird, and D. B. Rubin. Maximum Likelihood from Incomplete Data via the EM Algorithm. Journal of the Royal Statistical Society B, 39(1):1-22, 1977.
-
(1977)
Journal of the Royal Statistical Society B
, vol.39
, Issue.1
, pp. 1-22
-
-
Dempster, A.P.1
Laird, N.M.2
Rubin, D.B.3
-
11
-
-
4243137056
-
Hybrid Monte Carlo
-
S. Duane, A. D. Kennedy, B. J. Pendleton, and D. Roweth. Hybrid Monte Carlo. Physics Letters B, 195:216-222, 1995.
-
(1995)
Physics Letters B
, vol.195
, pp. 216-222
-
-
Duane, S.1
Kennedy, A.D.2
Pendleton, B.J.3
Roweth, D.4
-
14
-
-
0034592781
-
Data selection for support vector machine classifiers
-
also: Data Mining Institute Technical Report 00-02, University of Wisconsin, Madison
-
G. Fung and O. L. Mangasarian. Data selection for support vector machine classifiers. In Proceedings of KDD'2000, 2000. also: Data Mining Institute Technical Report 00-02, University of Wisconsin, Madison.
-
(2000)
Proceedings of KDD'2000
-
-
Fung, G.1
Mangasarian, O.L.2
-
15
-
-
0004012196
-
-
Chapman and Hall, London
-
A. Gelman, J. B. Carlin, H. S. Stern, and D. B. Rubin. Bayesian Data Analysis. Chapman and Hall, London, 1995.
-
(1995)
Bayesian Data Analysis
-
-
Gelman, A.1
Carlin, J.B.2
Stern, H.S.3
Rubin, D.B.4
-
20
-
-
0345338764
-
-
A.I. Memo 1287, Artificial Intelligence Laboratory, Massachusetts Institute of Technology
-
F. Girosi. Models of noise and robust estimates. A.I. Memo 1287, Artificial Intelligence Laboratory, Massachusetts Institute of Technology, 1991.
-
(1991)
Models of Noise and Robust Estimates
-
-
Girosi, F.1
-
22
-
-
0004236492
-
-
John Hopkins University Press, Baltimore, MD, 3rd edition
-
G. H. Golub and C. F. Van Loan. Matrix Computations. John Hopkins University Press, Baltimore, MD, 3rd edition, 1996.
-
(1996)
Matrix Computations
-
-
Golub, G.H.1
Van Loan, C.F.2
-
24
-
-
84899020966
-
Classification on pairwise proximity data
-
M. S. Kearns, S. A. Solla, and D. A. Cohn, editors, Cambridge, MA, MIT Press
-
T. Graepel, R. Herbrich, P. Bollmann-Sdorra, and K. Obermayer. Classification on pairwise proximity data. In M. S. Kearns, S. A. Solla, and D. A. Cohn, editors, Advances in Neural Information Processing Systems 11, pages 438-444, Cambridge, MA, 1999. MIT Press.
-
(1999)
Advances in Neural Information Processing Systems
, vol.11
, pp. 438-444
-
-
Graepel, T.1
Herbrich, R.2
Bollmann-Sdorra, P.3
Obermayer, K.4
-
25
-
-
0008267184
-
-
Technical Report UCSC-CRL-99-10, Computer Science Department, UC Santa Cruz
-
D. Haussler. Convolutional kernels on discrete structures. Technical Report UCSC-CRL-99-10, Computer Science Department, UC Santa Cruz, 1999.
-
(1999)
Convolutional Kernels on Discrete Structures
-
-
Haussler, D.1
-
27
-
-
0003035079
-
Thore Graepel, and Colin Campbell. Bayes point machines: Estimating the Bayes point in kernel space
-
Ralf Herbrich, Thore Graepel, and Colin Campbell. Bayes point machines: Estimating the Bayes point in kernel space. In Proceedings of IJCAI Workshop Support Vector Machines, pages 23-27, 1999.
-
(1999)
Proceedings of IJCAI Workshop Support Vector Machines
, pp. 23-27
-
-
Herbrich, R.1
-
29
-
-
0000171374
-
Robust statistics: A review
-
P. J. Huber. Robust statistics: a review. Annals of Statistics, 43:1041, 1972.
-
(1972)
Annals of Statistics
, vol.43
, pp. 1041
-
-
Huber, P.J.1
-
30
-
-
0008312225
-
-
Technical Report AITR-1668, Artificial Intelligence Laboratory, Massachusetts Institute of Technology
-
T. Jaakkola, M. Meila, and T. Jebara. Maximum entropy discrimination. Technical Report AITR-1668, Artificial Intelligence Laboratory, Massachusetts Institute of Technology, 1999.
-
(1999)
Maximum Entropy Discrimination
-
-
Jaakkola, T.1
Meila, M.2
Jebara, T.3
-
31
-
-
84898982939
-
Exploiting generative models in discriminative classifiers
-
M. S. Kearns, S. A. Solla, and D. A. Cohn, editors, Cambridge, MA, MIT Press
-
T. S. Jaakkola and D. Haussler. Exploiting generative models in discriminative classifiers. In M. S. Kearns, S. A. Solla, and D. A. Cohn, editors, Advances in Neural Information Processing Systems 11, pages 487-493, Cambridge, MA, 1999. MIT Press.
-
(1999)
Advances in Neural Information Processing Systems
, vol.11
, pp. 487-493
-
-
Jaakkola, T.S.1
Haussler, D.2
-
33
-
-
0001486499
-
Estimation with quadratic loss
-
Berkeley, University of California Press
-
W. James and C. Stein. Estimation with quadratic loss. In Proceedings of the Fourth Berkeley Symposium on Mathematics, Statistics and Probability, volume 1, pages 361-380, Berkeley, 1960. University of California Press.
-
(1960)
Proceedings of the Fourth Berkeley Symposium on Mathematics, Statistics and Probability
, vol.1
, pp. 361-380
-
-
James, W.1
Stein, C.2
-
36
-
-
0000935895
-
An introduction to variational methods for graphical models
-
M.I. Jordan, Kluwer Academic
-
M. I. Jordan, Z. Gharamani, T. S. Jaakkola, and L. K. Saul. An introduction to variational methods for graphical models. In Learning in Graphical Models, volume M.I. Jordan, pages 105-162. Kluwer Academic, 1998.
-
(1998)
Learning in Graphical Models
, pp. 105-162
-
-
Jordan, M.I.1
Gharamani, Z.2
Jaakkola, T.S.3
Saul, L.K.4
-
37
-
-
84898976425
-
Learning nonlinear overcomplete representations for efficient coding
-
M. I. Jordan, M. J. Kearns, and S. A. Solla, editors, Cambridge, MA, MIT Press
-
M. S. Lewicki and T. J. Sejnowski. Learning nonlinear overcomplete representations for efficient coding. In M. I. Jordan, M. J. Kearns, and S. A. Solla, editors, Advances in Neural Information Processing Systems 10, pages 556-562, Cambridge, MA, 1998. MIT Press.
-
(1998)
Advances in Neural Information Processing Systems
, vol.10
, pp. 556-562
-
-
Lewicki, M.S.1
Sejnowski, T.J.2
-
40
-
-
0003748256
-
-
PhD thesis, Computation and Neural Systems, California Institute of Technology, Pasadena, CA
-
D. J. C. MacKay. Bayesian Methods for Adaptive Models. PhD thesis, Computation and Neural Systems, California Institute of Technology, Pasadena, CA, 1991.
-
(1991)
Bayesian Methods for Adaptive Models
-
-
MacKay, D.J.C.1
-
41
-
-
0000234257
-
The evidence framework applied to classification networks
-
D. J. C. MacKay. The evidence framework applied to classification networks. Neural Computation, 4(5):720-736, 1992.
-
(1992)
Neural Computation
, vol.4
, Issue.5
, pp. 720-736
-
-
MacKay, D.J.C.1
-
43
-
-
0000963583
-
Linear and nonlinear separation of patterns by linear programming
-
O. L. Mangasarian. Linear and nonlinear separation of patterns by linear programming. Operations Research, 13:444-452, 1965.
-
(1965)
Operations Research
, vol.13
, pp. 444-452
-
-
Mangasarian, O.L.1
-
44
-
-
0029291966
-
Sparse approximate solutions to linear systems
-
B. K. Natarajan. Sparse approximate solutions to linear systems. SIAM Journal of Computing, 25(2):227-234, 1995.
-
(1995)
SIAM Journal of Computing
, vol.25
, Issue.2
, pp. 227-234
-
-
Natarajan, B.K.1
-
45
-
-
0242427913
-
-
Technical Report CRG-TR-94-1, Dept. of Computer Science, University of Toronto
-
R. Neal. Priors for infinite networks. Technical Report CRG-TR-94-1, Dept. of Computer Science, University of Toronto, 1994.
-
(1994)
Priors for Infinite Networks
-
-
Neal, R.1
-
48
-
-
0029938380
-
Emergence of simple-cell receptive field properties by learning a sparse code for natural images
-
B. A. Olshausen and D. J. Field. Emergence of simple-cell receptive field properties by learning a sparse code for natural images. Nature, 381:607-609, 1996.
-
(1996)
Nature
, vol.381
, pp. 607-609
-
-
Olshausen, B.A.1
Field, D.J.2
-
49
-
-
0039814276
-
Mean field methods for classification with Gaussian processes
-
M. S. Kearns, S. A. Solla, and D. A. Cohn, editors, Cambridge, MA, MIT Press
-
M. Opper and O. Winther. Mean field methods for classification with Gaussian processes. In M. S. Kearns, S. A. Solla, and D. A. Cohn, editors, Advances in Neural Information Processing Systems 11, pages 309-315, Cambridge, MA, 1999. MIT Press.
-
(1999)
Advances in Neural Information Processing Systems
, vol.11
, pp. 309-315
-
-
Opper, M.1
Winther, O.2
-
50
-
-
0002755771
-
Gaussian processes and SVM: Mean field and leave-one-out
-
A. J. Smola, P. L. Bartlett, B. Schölkopf, and D. Schuurmans, editors, Cambridge, MA, MIT Press
-
M. Opper and O. Winther. Gaussian processes and SVM: mean field and leave-one-out. In A. J. Smola, P. L. Bartlett, B. Schölkopf, and D. Schuurmans, editors, Advances in Large Margin Classifiers, pages 311-326, Cambridge, MA, 2000. MIT Press.
-
(2000)
Advances in Large Margin Classifiers
, pp. 311-326
-
-
Opper, M.1
Winther, O.2
-
51
-
-
0003243224
-
Probabilities for SV machines
-
A. J. Smola, P. L. Bartlett, B. Schölkopf, and D. Schuurmans, editors, Cambridge, MA, MIT Press
-
J. Platt. Probabilities for SV machines. In A. J. Smola, P. L. Bartlett, B. Schölkopf, and D. Schuurmans, editors, Advances in Large Margin Classifiers, pages 61-73, Cambridge, MA, 2000. MIT Press.
-
(2000)
Advances in Large Margin Classifiers
, pp. 61-73
-
-
Platt, J.1
-
52
-
-
0016765357
-
On optimal nonlinear associative recall
-
T. Poggio. On optimal nonlinear associative recall. Biological Cybernetics, 19:201-209, 1975.
-
(1975)
Biological Cybernetics
, vol.19
, pp. 201-209
-
-
Poggio, T.1
-
53
-
-
0004161838
-
-
Cambridge University Press, Cambridge, ISBN 0-521-43108-5
-
W. H. Press, S. A. Teukolsky, W. T. Vetterling, and B. P. Flannery. Numerical Recipes in C: The Art of Scientific Computing (2nd ed.). Cambridge University Press, Cambridge, 1992. ISBN 0-521-43108-5.
-
(1992)
Numerical Recipes in C: the Art of Scientific Computing (2nd Ed.)
-
-
Press, W.H.1
Teukolsky, S.A.2
Vetterling, W.T.3
Flannery, B.P.4
-
57
-
-
0003346020
-
Convex Analysis
-
Princeton University Press
-
R. T. Rockafellar. Convex Analysis, volume 28 of Princeton Mathematics Series. Princeton University Press, 1970.
-
(1970)
Princeton Mathematics Series
, vol.28
-
-
Rockafellar, R.T.1
-
58
-
-
0013406706
-
Computing the Bayes kernel classifier
-
A. J. Smola, P. L. Bartlett, B. Schölkopf, and D. Schuurmans, editors, Cambridge, MA, MIT Press
-
P. Ruján and M. Marchand. Computing the Bayes kernel classifier. In A. J. Smola, P. L. Bartlett, B. Schölkopf, and D. Schuurmans, editors, Advances in Large Margin Classifiers, pages 329-347, Cambridge, MA, 2000. MIT Press.
-
(2000)
Advances in Large Margin Classifiers
, pp. 329-347
-
-
Ruján, P.1
Marchand, M.2
-
59
-
-
0002536264
-
Playing billiards in version space
-
Pál Ruján. Playing billiards in version space. Neural Computation, 9:99-122, 1997.
-
(1997)
Neural Computation
, vol.9
, pp. 99-122
-
-
Ruján, P.1
-
60
-
-
0032594954
-
Input space vs. feature space in kernel-based methods
-
B. Schölkopf, S. Mika, C. Burges, P. Knirsch, K.-R. Müller, G. Rätsch, and A. Smola. Input space vs. feature space in kernel-based methods. IEEE Transactions on Neural Networks, 10(5):1000-1017, 1999.
-
(1999)
IEEE Transactions on Neural Networks
, vol.10
, Issue.5
, pp. 1000-1017
-
-
Schölkopf, B.1
Mika, S.2
Burges, C.3
Knirsch, P.4
Müller, K.-R.5
Rätsch, G.6
Smola, A.7
-
61
-
-
0002570938
-
Kernel principal component analysis
-
B. Schölkopf, C. J. C. Burges, and A. J. Smola, editors, MIT Press, Cambridge, MA
-
B. Schölkopf, A. Smola, and K.-R. Müller. Kernel principal component analysis. In B. Schölkopf, C. J. C. Burges, and A. J. Smola, editors, Advances in Kernel Methods - Support Vector Learning, pages 327-352. MIT Press, Cambridge, MA, 1999.
-
(1999)
Advances in Kernel Methods - Support Vector Learning
, pp. 327-352
-
-
Schölkopf, B.1
Smola, A.2
Müller, K.-R.3
-
65
-
-
0033339941
-
Linear programs for automatic accuracy control in regression
-
Conference Publications No. 470, London, IEE
-
A. Smola, B. Schölkopf, and G. Rätsch. Linear programs for automatic accuracy control in regression. In Ninth International Conference on Artificial Neural Networks, Conference Publications No. 470, pages 575-580, London, 1999. IEE.
-
(1999)
Ninth International Conference on Artificial Neural Networks
, pp. 575-580
-
-
Smola, A.1
Schölkopf, B.2
Rätsch, G.3
-
66
-
-
0004094721
-
-
PhD thesis, Technische Universität Berlin, GMD Research Series No. 25
-
A. J. Smola. Learning with Kernels. PhD thesis, Technische Universität Berlin, 1998. GMD Research Series No. 25.
-
(1998)
Learning with Kernels
-
-
Smola, A.J.1
-
67
-
-
84899000575
-
Sparse greedy Gaussian process regression
-
T. K. Leen, T. G. Dietterich, and V. Tresp, editors, MIT Press
-
A. J. Smola and P. L. Bartlett. Sparse greedy Gaussian process regression. In T. K. Leen, T. G. Dietterich, and V. Tresp, editors, Advances in Neural Information Processing Systems 13, pages 619-625. MIT Press, 2001.
-
(2001)
Advances in Neural Information Processing Systems
, vol.13
, pp. 619-625
-
-
Smola, A.J.1
Bartlett, P.L.2
-
68
-
-
0002493574
-
Sparse greedy matrix approximation for machine learning
-
P. Langley, editor, San Francisco, Morgan Kaufmann Publishers
-
A. J. Smola and B. Schölkopf. Sparse greedy matrix approximation for machine learning. In P. Langley, editor, Proceedings of the International Conference on Machine Learning, pages 911-918, San Francisco, 2000. Morgan Kaufmann Publishers.
-
(2000)
Proceedings of the International Conference on Machine Learning
, pp. 911-918
-
-
Smola, A.J.1
Schölkopf, B.2
-
69
-
-
35248820396
-
Cholesky factorization for rank-k modifications of diagonal matrices
-
submitted
-
A.J. Smola and S.V.N. Vishwanathan. Cholesky factorization for rank-k modifications of diagonal matrices. SIAM Journal of Matrix Analysis, 2002. submitted.
-
(2002)
SIAM Journal of Matrix Analysis
-
-
Smola, A.J.1
Vishwanathan, S.V.N.2
-
71
-
-
84986980101
-
Sequential updating of conditional probabilities on directed graphical structures
-
D. J. Spiegelhalter and S. L. Lauritzen. Sequential updating of conditional probabilities on directed graphical structures. Networks, 20:579-605, 1990.
-
(1990)
Networks
, vol.20
, pp. 579-605
-
-
Spiegelhalter, D.J.1
Lauritzen, S.L.2
-
73
-
-
0001224048
-
Sparse Bayesian learning and the relevance vector machine
-
M. Tipping. Sparse Bayesian learning and the relevance vector machine. Journal of Machine Learning Research, 1:211-244, 2001.
-
(2001)
Journal of Machine Learning Research
, vol.1
, pp. 211-244
-
-
Tipping, M.1
-
74
-
-
0034320395
-
A Bayesian committee machine
-
V. Tresp. A Bayesian committee machine. Neural Computation, 12(11):2719-2741, 2000.
-
(2000)
Neural Computation
, vol.12
, Issue.11
, pp. 2719-2741
-
-
Tresp, V.1
-
76
-
-
84887252594
-
Support vector method for function approximation, regression estimation, and signal processing
-
M. C. Mozer, M. I. Jordan, and T. Petsche, editors, Cambridge, MA, MIT Press
-
V. Vapnik, S. Golowich, and A. Smola. Support vector method for function approximation, regression estimation, and signal processing. In M. C. Mozer, M. I. Jordan, and T. Petsche, editors, Advances in Neural Information Processing Systems 9, pages 281-287, Cambridge, MA, 1997. MIT Press.
-
(1997)
Advances in Neural Information Processing Systems
, vol.9
, pp. 281-287
-
-
Vapnik, V.1
Golowich, S.2
Smola, A.3
-
78
-
-
0004202459
-
-
CSD-TR-98- 11, Royal Holloway, University of London, Egham, Surrey, UK
-
C. Watkins. Dynamic alignment kernels. CSD-TR-98- 11, Royal Holloway, University of London, Egham, Surrey, UK, 1999.
-
(1999)
Dynamic Alignment Kernels
-
-
Watkins, C.1
-
80
-
-
0003017575
-
Prediction with Gaussian processes: From linear regression to linear prediction and beyond
-
M. I. Jordan, editor, Kluwer Academic
-
C. K. I. Williams. Prediction with Gaussian processes: From linear regression to linear prediction and beyond. In M. I. Jordan, editor, Learning and Inference in Graphical Models. Kluwer Academic, 1998.
-
(1998)
Learning and Inference in Graphical Models
-
-
Williams, C.K.I.1
-
81
-
-
0003017575
-
Prediction with Gaussian processes: From linear regression to linear prediction and beyond
-
Micheal Jordan, editor, MIT Press
-
C. K. I. Williams. Prediction with Gaussian processes: From linear regression to linear prediction and beyond. In Micheal Jordan, editor, Learning and Inference in Graphical Models, pages 599-621. MIT Press, 1999.
-
(1999)
Learning and Inference in Graphical Models
, pp. 599-621
-
-
Williams, C.K.I.1
-
82
-
-
85072768928
-
Gaussian processes for regression
-
D. S. Touretzky, M. C. Mozer, and M. E. Hasselmo, editors, Cambridge, MA, MIT Press
-
C. K. I. Williams and C. E. Rasmussen. Gaussian processes for regression. In D. S. Touretzky, M. C. Mozer, and M. E. Hasselmo, editors, Advances in Neural Information Processing Systems 8, pages 514-520, Cambridge, MA, 1996. MIT Press.
-
(1996)
Advances in Neural Information Processing Systems
, vol.8
, pp. 514-520
-
-
Williams, C.K.I.1
Rasmussen, C.E.2
-
83
-
-
84899010839
-
Using the Nystrom method to speed up kernel machines
-
T. K. Leen, T. G. Dietterich, and V. Tresp, editors, Cambridge, MA, MIT Press
-
Christoper K. I. Williams and Matthias Seeger. Using the Nystrom method to speed up kernel machines. In T. K. Leen, T. G. Dietterich, and V. Tresp, editors, Advances in Neural Information Processing Systems 13, pages 682-688, Cambridge, MA, 2001. MIT Press.
-
(2001)
Advances in Neural Information Processing Systems
, vol.13
, pp. 682-688
-
-
Williams, C.K.I.1
Seeger, M.2
-
85
-
-
0141819626
-
Some sparse approximation bounds for regression problems
-
Morgan Kaufmann, San Francisco, CA
-
T. Zhang. Some sparse approximation bounds for regression problems. In Proc. 18th International Conf. on Machine Learning, pages 624-631. Morgan Kaufmann, San Francisco, CA, 2001.
-
(2001)
Proc. 18th International Conf. on Machine Learning
, pp. 624-631
-
-
Zhang, T.1
|