-
1
-
-
84864063089
-
-
B. Schölkopf, J. Platt,&T.Hoffman (Eds.), Multi-task feature learning, Cambrige, MA: MIT Press
-
Argyriou, A., Evgeniou, T.,&Pontil, M. (2007). In B. Schölkopf, J. Platt,&T.Hoffman (Eds.), Multi-task feature learning. In Advances in neural information processing systems, 19. Cambrige, MA: MIT Press.
-
(2007)
Advances in neural information processing systems
, pp. 19
-
-
Argyriou, A.1
Evgeniou, T.2
Pontil, M.3
-
3
-
-
84880203756
-
Laplacian eigenmaps and spectral techniques for embedding and clustering
-
T. C. Dietterich, S. Becker, & Z. Ghahramani (Eds.), Cambridge, MA: MIT Press
-
Belkin, M., & Niyogi, P. (2002). Laplacian eigenmaps and spectral techniques for embedding and clustering. In T. C. Dietterich, S. Becker, & Z. Ghahramani (Eds.), Advances in neural information processing systems, 14. Cambridge, MA: MIT Press.
-
(2002)
Advances in neural information processing systems
, pp. 14
-
-
Belkin, M.1
Niyogi, P.2
-
6
-
-
0002652285
-
A maximum entropy approach to natural language processing
-
Berger, A., Pietra, S., & Pietra, V. (1996). A maximum entropy approach to natural language processing. Computational Linguistics, 22, 39-71.
-
(1996)
Computational Linguistics
, vol.22
, pp. 39-71
-
-
Berger, A.1
Pietra, S.2
Pietra, V.3
-
9
-
-
34547996209
-
Information-theoretic metric learning
-
Madison, WI: Omni Press
-
Davis, J., Kulis, B., Jain, P., Sra, S., & Dhillon, I. (2007). Information-theoretic metric learning. In Proceedings of the 24th International Conference on Machine Learning. Madison, WI: Omni Press.
-
(2007)
Proceedings of the 24th International Conference on Machine Learning
-
-
Davis, J.1
Kulis, B.2
Jain, P.3
Sra, S.4
Dhillon, I.5
-
11
-
-
0000764772
-
The use of multiple measurements in taxonomic problems
-
Fisher, R. A. (1936). The use of multiple measurements in taxonomic problems. Annals of Eugenics, 7(2), 179-188.
-
(1936)
Annals of Eugenics
, vol.7
, Issue.2
, pp. 179-188
-
-
Fisher, R.A.1
-
12
-
-
68649121147
-
Kernel dimension reduction in regression
-
Fukumizu, K., Bach, F., & Jordan,M. I. (2009) Kernel dimension reduction in regression. Annals of Statistics, 37(4), 1871-1905.
-
(2009)
Annals of Statistics
, vol.37
, Issue.4
, pp. 1871-1905
-
-
Fukumizu, K.1
Bach, F.2
Jordan, M.I.3
-
13
-
-
79952741539
-
Posterior sparsity in usupervised dependency parsing
-
Gillenwater, J., Ganchev, K., Graça, J., Pereira, F., & Taskar, B. (2011). Posterior sparsity in usupervised dependency parsing. Journal ofMachine Learning Research, 12, 455-490.
-
(2011)
Journal ofMachine Learning Research
, vol.12
, pp. 455-490
-
-
Gillenwater, J.1
Ganchev, K.2
Graça, J.3
Pereira, F.4
Taskar, B.5
-
14
-
-
33749236726
-
Metric learning by collapsing classes
-
Y.Weiss, B. Schölkopf, & J. Platt (Eds.), Cambridge, MA: MIT Press
-
Globerson, A., & Roweis, S. (2006).Metric learning by collapsing classes. In Y.Weiss, B. Schölkopf, & J. Platt (Eds.), Advances in neural information processing systems, 18. Cambridge, MA: MIT Press.
-
(2006)
Advances in neural information processing systems
, pp. 18
-
-
Globerson, A.1
Roweis, S.2
-
15
-
-
84898993653
-
Neighbourhood components analysis
-
L. K. Saul, Y. Weiss, & J. Platt (Eds.), Cambridge, MA: MIT Press
-
Goldberger, J., Roweis, S., Hinton, G., & Salakhutdinov, R. (2005). Neighbourhood components analysis. In L. K. Saul, Y. Weiss, & J. Platt (Eds.), Advances in neural information processing systems, 17. Cambridge, MA: MIT Press.
-
(2005)
Advances in neural information processing systems
, pp. 17
-
-
Goldberger, J.1
Roweis, S.2
Hinton, G.3
Salakhutdinov, R.4
-
16
-
-
85161986160
-
Discriminative clustering by regularized information maximization
-
J. Lafferty (Ed.), Red Hook, NY: Curran
-
Gomes, R., Krause, A., & Perona, P. (2010). Discriminative clustering by regularized information maximization. In J. Lafferty (Ed.), Advances in neural information processing systems, 23. Red Hook, NY: Curran.
-
(2010)
Advances in neural information processing systems
, pp. 23
-
-
Gomes, R.1
Krause, A.2
Perona, P.3
-
17
-
-
85162012703
-
Expectation maximization and posterior constraints
-
J. C. Platt, D. Köller, Y. Singer, & S. Roweis (Eds.), Cambridge, MA: MIT Press
-
Graça, J., Ganchev, K., & Taskar, B. (2008). Expectation maximization and posterior constraints. In J. C. Platt, D. Köller, Y. Singer, & S. Roweis (Eds.), Advances in neural information processing systems, 20. Cambridge, MA: MIT Press.
-
(2008)
Advances in neural information processing systems
, pp. 20
-
-
Graça, J.1
Ganchev, K.2
Taskar, B.3
-
18
-
-
80053292525
-
Posterior vs. parameter sparsity in latent variable models
-
Y. Bengio, D. Schuurmans, J. Lafferty, C. Williams, & A. Culota (Eds.)
-
Graça, J., Ganchev, K., Taskar, B.,&Pereira, F. (2009). Posterior vs. parameter sparsity in latent variable models. In Y. Bengio, D. Schuurmans, J. Lafferty, C. Williams, & A. Culota (Eds.), Advances in neural information processing systems, 22.
-
(2009)
Advances in neural information processing systems
, pp. 22
-
-
Graça, J.1
Ganchev, K.2
Taskar, B.3
Pereira, F.4
-
19
-
-
84898928156
-
Semi-supervised learning by entropy minimization
-
L. K. Saul, Y. Weiss, & L. Bottou (Eds.), Cambridge, MA: MIT Press
-
Grandvalet, Y., & Bengio, Y. (2005). Semi-supervised learning by entropy minimization. In L. K. Saul, Y. Weiss, & L. Bottou (Eds.), Advances in neural information processing systems, 17. Cambridge, MA: MIT Press.
-
(2005)
Advances in neural information processing systems
, pp. 17
-
-
Grandvalet, Y.1
Bengio, Y.2
-
20
-
-
77956504247
-
Entropy regularization
-
O. Chapelle, B. Schölkopf, & A. Zien (Eds.), Cambridge, MA: MIT Press
-
Grandvalet, Y., & Bengio, Y. (2006). Entropy regularization. In O. Chapelle, B. Schölkopf, & A. Zien (Eds.), Semi-supervised learning (pp. 151-168). Cambridge, MA: MIT Press.
-
(2006)
Semi-supervised learning
, pp. 151-168
-
-
Grandvalet, Y.1
Bengio, Y.2
-
21
-
-
51949106897
-
Semi-supervised distance metric learning for collaborative image retrieval
-
Piscataway, NJ: IEEE Press
-
Hoi, S., Liu, W., & Chang, S.-F. (2008). Semi-supervised distance metric learning for collaborative image retrieval. In Proceedings of the 21st IEEE Conference on Computer Vision and Pattern Recognition. Piscataway, NJ: IEEE Press.
-
(2008)
Proceedings of the 21st IEEE Conference on Computer Vision and Pattern Recognition
-
-
Hoi, S.1
Liu, W.2
Chang, S.-F.3
-
22
-
-
80053134215
-
Robust metric learning by smooth optimization
-
San Francisco: Morgan Kaufmann
-
Huang, K., Jin, R., Xu, Z., & Liu, C. (2010). Robust metric learning by smooth optimization. In Proceedings of the 26thConference on Uncertainty inArtificial Intelligence. San Francisco: Morgan Kaufmann.
-
(2010)
Proceedings of the 26thConference on Uncertainty inArtificial Intelligence
-
-
Huang, K.1
Jin, R.2
Xu, Z.3
Liu, C.4
-
24
-
-
85162055589
-
Inductive regularized learning of kernel functions
-
J. Lafferty (Ed.), Red Hook, NY: Curran
-
Jain, P., Kulis, B., & Dhillon, I. (2010) Inductive regularized learning of kernel functions. In J. Lafferty (Ed.), Advances in neural information processing systems, 23. Red Hook, NY: Curran.
-
(2010)
Advances in neural information processing systems
, pp. 23
-
-
Jain, P.1
Kulis, B.2
Dhillon, I.3
-
25
-
-
11944266539
-
Information theory and statistical mechanics
-
Jaynes, E. T. (1957). Information theory and statistical mechanics. Physical Review, 106(4), 620-630.
-
(1957)
Physical Review
, vol.106
, Issue.4
, pp. 620-630
-
-
Jaynes, E.T.1
-
26
-
-
77956207894
-
Semi-supervised sparse metric learning using alternating linearization optimization
-
NewYork: ACM Press
-
Liu, W., Ma, S., Tao, D., Liu, J., & Liu, P. (2010). Semi-supervised sparse metric learning using alternating linearization optimization. In Proceedings of the 16th ACM International Conference on Knowledge Discovery and DataMining. NewYork: ACM Press.
-
(2010)
Proceedings of the 16th ACM International Conference on Knowledge Discovery and DataMining
-
-
Liu, W.1
Ma, S.2
Tao, D.3
Liu, J.4
Liu, P.5
-
27
-
-
84867125343
-
Information-theoretic semisupervised metric learning via entropy regularization
-
Madison, WI:Omni Press
-
Niu, G., Dai, B., Yamada, M., & Sugiyama, M. (2012). Information-theoretic semisupervised metric learning via entropy regularization. In Proceedings of the 29th International Conference on Machine Learning. Madison, WI:Omni Press.
-
(2012)
Proceedings of the 29th International Conference on Machine Learning
-
-
Niu, G.1
Dai, B.2
Yamada, M.3
Sugiyama, M.4
-
28
-
-
0010041380
-
A general method for solving extremal problems (in Russian)
-
Polyak, B. T. (1967) A general method for solving extremal problems (in Russian). Soviet Mathematics Doklady, 174(1), 33-36.
-
(1967)
Soviet Mathematics Doklady
, vol.174
, Issue.1
, pp. 33-36
-
-
Polyak, B.T.1
-
29
-
-
0034704222
-
Nonlinear dimensionality reduction by locally linear embedding
-
Roweis, S., & Saul, L. (2000). Nonlinear dimensionality reduction by locally linear embedding. Science, 290, 2323-2326.
-
(2000)
Science
, vol.290
, pp. 2323-2326
-
-
Roweis, S.1
Saul, L.2
-
31
-
-
34249086815
-
Dimensionality reduction of multimodal labeled data by local Fisher discriminant analysis
-
Sugiyama, M. (2007). Dimensionality reduction of multimodal labeled data by local Fisher discriminant analysis. Journal of Machine Learning Research, 8, 1027-1061.
-
(2007)
Journal of Machine Learning Research
, vol.8
, pp. 1027-1061
-
-
Sugiyama, M.1
-
32
-
-
77952423823
-
Semi-supervised local Fisher discriminant analysis for dimensionality reduction
-
Sugiyama, M., Idé, T., Nakajima, S., & Sese, J. (2010). Semi-supervised local Fisher discriminant analysis for dimensionality reduction. Machine Learning, 78(1-2), 35-61.
-
(2010)
Machine Learning
, vol.78
, Issue.1-2
, pp. 35-61
-
-
Sugiyama, M.1
Idé, T.2
Nakajima, S.3
Sese, J.4
-
33
-
-
0034704229
-
A global geometric framework for nonlinear dimensionality reduction
-
Tenenbaum, J., de Silva, V., & Langford, J. (2000). A global geometric framework for nonlinear dimensionality reduction. Science, 290, 2319-2323.
-
(2000)
Science
, vol.290
, pp. 2319-2323
-
-
Tenenbaum, J.1
de Silva, V.2
Langford, J.3
-
34
-
-
84864062501
-
Large margin component analysis
-
B. Schölkopf, J. Platt, & T. Hoffman (Eds.), Cambridge, MA: MIT Press
-
Torresani, L., & Lee, K. (2007). Large margin component analysis. In B. Schölkopf, J. Platt, & T. Hoffman (Eds.), Advances in neural information processing systems, 19. Cambridge, MA: MIT Press.
-
(2007)
Advances in neural information processing systems
, pp. 19
-
-
Torresani, L.1
Lee, K.2
-
35
-
-
85162550129
-
Metric learning with multiple kernels
-
J. Shawe-Taylor, R. S. Zemel, P. L. Bartlett, F. C. N Pereira, & Q. Weinberger (Eds.), Red Hook, NY: Curran
-
Wang, J., Do, H., Woznica, A., & Kalousis, A. (2011). Metric learning with multiple kernels. In J. Shawe-Taylor, R. S. Zemel, P. L. Bartlett, F. C. N Pereira, & Q. Weinberger (Eds.), Advances in neural information processing systems, 24. Red Hook, NY: Curran.
-
(2011)
Advances in neural information processing systems
, pp. 24
-
-
Wang, J.1
Do, H.2
Woznica, A.3
Kalousis, A.4
-
36
-
-
33749550361
-
Distancemetric learning for large margin nearest neighbor classification
-
Y.Weiss, B. Schölkopf,&J. Platt (Eds.), Cambridge, MA: MIT Press
-
Weinberger, K., Blitzer, J.,&Saul, L. (2006).Distancemetric learning for large margin nearest neighbor classification. In Y.Weiss, B. Schölkopf,&J. Platt (Eds.), Advances in neural information processing systems, 18. Cambridge, MA: MIT Press.
-
(2006)
Advances in neural information processing systems
, pp. 18
-
-
Weinberger, K.1
Blitzer, J.2
Saul, L.3
-
37
-
-
84879571292
-
Distance metric learning with application to clustering with side-information
-
S. Becker, S. Thrün, & K. Obermayer (Eds.), Cambridge, MA: MIT Press
-
Xing, E., Ng, A., Jordan, M. I., & Russell, S. (2003). Distance metric learning with application to clustering with side-information. In S. Becker, S. Thrün, & K. Obermayer (Eds.), Advances in neural information processing systems, 15. Cambridge, MA: MIT Press.
-
(2003)
Advances in neural information processing systems
, pp. 15
-
-
Xing, E.1
Ng, A.2
Jordan, M.I.3
Russell, S.4
-
38
-
-
33750707555
-
An efficient algorithm for local distance metric learning
-
Menlo Park, CA: AAAI Press
-
Yang, L., Jin, R., Sukthankar, R., & Liu, Y. (2006). An efficient algorithm for local distance metric learning. In Proceedings of the 21st National Conference on Artificial Intelligence. Menlo Park, CA: AAAI Press.
-
(2006)
Proceedings of the 21st National Conference on Artificial Intelligence
-
-
Yang, L.1
Jin, R.2
Sukthankar, R.3
Liu, Y.4
-
39
-
-
79957815549
-
Sparse metric learning via smooth optimization
-
Y. Bengio, D. Schuurmans, J. Lafferty, C. Williams, & A. Culota (Eds.)
-
Ying, Y., Huang, K., & Campbell, C. (2009). Sparse metric learning via smooth optimization. In Y. Bengio, D. Schuurmans, J. Lafferty, C. Williams, & A. Culota (Eds.), Advances in neural information processing systems, 22.
-
(2009)
Advances in neural information processing systems
, pp. 22
-
-
Ying, Y.1
Huang, K.2
Campbell, C.3
-
40
-
-
33645035051
-
Model selection and estimation in regression with grouped variables
-
Yuan,M. & Lin, Y. (2006) Model selection and estimation in regression with grouped variables. Journal of the Royal Statistical Society, Series B, 68 (1), 49-67.
-
(2006)
Journal of the Royal Statistical Society, Series B
, vol.68
, Issue.1
, pp. 49-67
-
-
Yuan, M.1
Lin, Y.2
-
41
-
-
77956224771
-
Robustdistancemetric learning with auxiliary knowledge
-
Menlo Park, CA: AAAI Press
-
Zha,Z., Mei,T.,Wang, M.,Wang, Z.,&Hua, X. (2009).Robustdistancemetric learning with auxiliary knowledge. In Proceedings of 21st International Joint Conference on Artificial Intelligence. Menlo Park, CA: AAAI Press.
-
(2009)
Proceedings of 21st International Joint Conference on Artificial Intelligence
-
-
Zha, Z.1
Mei, T.2
Wang, M.3
Wang, Z.4
Hua, X.5
|