-
2
-
-
78751683598
-
Convex multitask feature learning
-
press
-
A. Argyriou, T. Evgeniou, M. Pontil, A. Argyriou, T. Evgeniou, and M. Pontil. Convex multitask feature learning. In Machine Learning. press, 2007.
-
(2007)
Machine Learning
-
-
Argyriou, A.1
Evgeniou, T.2
Pontil, M.3
Argyriou, A.4
Evgeniou, T.5
Pontil, M.6
-
3
-
-
73549115421
-
When is there a representer theorem? vector versus matrix regularizers
-
A. Argyriou, C. A. Micchelli, and M. Pontil. When is there a representer theorem? vector versus matrix regularizers. J. Mach. Learn. Res., 10:2507-2529, 2009.
-
(2009)
J. Mach. Learn. Res.
, vol.10
, pp. 2507-2529
-
-
Argyriou, A.1
Micchelli, C.A.2
Pontil, M.3
-
4
-
-
85162007328
-
A spectral regularization framework for multi-task structure learning
-
A. Argyriou, C. A. Micchelli, M. Pontil, and Y. Ying. A spectral regularization framework for multi-task structure learning. In NIPS '08. 2008.
-
(2008)
NIPS '08
-
-
Argyriou, A.1
Micchelli, C.A.2
Pontil, M.3
Ying, Y.4
-
5
-
-
0346238931
-
Task clustering and gating for bayesian multitask learning
-
2003
-
B. Bakker and T. Heskes. Task clustering and gating for bayesian multitask learning. JMLR, 4:2003, 2003.
-
(2003)
JMLR
, vol.4
-
-
Bakker, B.1
Heskes, T.2
-
6
-
-
0042378381
-
Laplacian eigenmaps for dimensionality reduction and data representation
-
M. Belkin and P. Niyogi. Laplacian eigenmaps for dimensionality reduction and data representation. Neural Computation, 15:1373-1396, 2002.
-
(2002)
Neural Computation
, vol.15
, pp. 1373-1396
-
-
Belkin, M.1
Niyogi, P.2
-
7
-
-
33750729556
-
Manifold regularization: A geometric framework for learning from labeled and unlabeled examples
-
M. Belkin, P. Niyogi, and V. Sindhwani. Manifold regularization: A geometric framework for learning from labeled and unlabeled examples. J. Mach. Learn. Res., 7:2399-2434, 2006.
-
(2006)
J. Mach. Learn. Res.
, vol.7
, pp. 2399-2434
-
-
Belkin, M.1
Niyogi, P.2
Sindhwani, V.3
-
8
-
-
0031189914
-
Multitask learning
-
R. Caruana. Multitask learning. In Machine Learning, pages 41-75, 1997.
-
(1997)
Machine Learning
, pp. 41-75
-
-
Caruana, R.1
-
10
-
-
21844456299
-
Learning multiple tasks with kernel methods
-
T. Evgeniou, C. A. Micchelli, and M. Pontil. Learning multiple tasks with kernel methods. JMLR, 6:615-637, 2005.
-
(2005)
JMLR
, vol.6
, pp. 615-637
-
-
Evgeniou, T.1
Micchelli, C.A.2
Pontil, M.3
-
13
-
-
84858783652
-
Clustered multi-task learning: A convex formulation
-
L. Jacob, F. Bach, and J.-P. Vert. Clustered multi-task learning: A convex formulation. In NIPS '08, 2008.
-
(2008)
NIPS '08
-
-
Jacob, L.1
Bach, F.2
Vert, J.-P.3
-
14
-
-
0030521288
-
Hierarchical bayes conjoint analysis: Recovery of partworth heterogeneity from reduced experimental designs
-
P. J. Lenk, W. S. DeSarbo, P. E. Green, and M. R. Young. Hierarchical bayes conjoint analysis: Recovery of partworth heterogeneity from reduced experimental designs. MARKETING SCIENCE, 1996.
-
(1996)
Marketing Science
-
-
Lenk, P.J.1
Desarbo, W.S.2
Green, P.E.3
Young, M.R.4
-
15
-
-
85161995347
-
-
IEEE 2009
-
Q. Liu, X. Liao, H. L. Carin, J. R. Stack, and L. Carin. Semisupervised multitask learning. IEEE 2009, 2009.
-
(2009)
Semisupervised Multitask Learning
-
-
Liu, Q.1
Liao, X.2
Carin, H.L.3
Stack, J.R.4
Carin, L.5
-
16
-
-
12244250351
-
Regularized multi-task learning
-
C. A. Micchelli and M. Pontil. Regularized multi-task learning. In KDD 2004, pages 109-117, 2004.
-
(2004)
KDD 2004
, pp. 109-117
-
-
Micchelli, C.A.1
Pontil, M.2
-
17
-
-
0034704222
-
Nonlinear dimensionality reduction by locally linear embedding
-
December
-
S. T. Roweis and L. K. Saul. Nonlinear dimensionality reduction by locally linear embedding. Science, 290(5500):2323-2326, December 2000.
-
(2000)
Science
, vol.290
, Issue.5500
, pp. 2323-2326
-
-
Roweis, S.T.1
Saul, L.K.2
-
18
-
-
0034704229
-
A global geometric framework for nonlinear dimensionality reduction
-
December
-
J. B. Tenenbaum, V. Silva, and J. C. Langford. A global geometric framework for nonlinear dimensionality reduction. Science, 290(5500):2319-2323, December 2000.
-
(2000)
Science
, vol.290
, Issue.5500
, pp. 2319-2323
-
-
Tenenbaum, J.B.1
Silva, V.2
Langford, J.C.3
-
19
-
-
0003901612
-
-
Kluwer Academic Publishers, Norwell, MA, USA
-
S. Thrun and L. Pratt, editors. Learning to learn. Kluwer Academic Publishers, Norwell, MA, USA, 1998.
-
(1998)
Learning to Learn
-
-
Thrun, S.1
Pratt, L.2
-
20
-
-
14344251006
-
Learning a kernel matrix for nonlinear dimensionality reduction
-
ACM Press
-
K. Q.Weinberger, F. Sha, and L. K. Saul. Learning a kernel matrix for nonlinear dimensionality reduction. In In ICML 2004, pages 839-846. ACM Press, 2004.
-
(2004)
ICML 2004
, pp. 839-846
-
-
Weinberger, K.Q.1
Sha, F.2
Saul, L.K.3
-
21
-
-
33846487387
-
Multi-task learning for classification with dirichlet process priors
-
Y. Xue, X. Liao, L. Carin, and B. Krishnapuram. Multi-task learning for classification with dirichlet process priors. J. Mach. Learn. Res., 8:35-63, 2007.
-
(2007)
J. Mach. Learn. Res.
, vol.8
, pp. 35-63
-
-
Xue, Y.1
Liao, X.2
Carin, L.3
Krishnapuram, B.4
-
22
-
-
31844442664
-
Learning gaussian processes from multiple tasks
-
K. Yu, V. Tresp, and A. Schwaighofer. Learning gaussian processes from multiple tasks. In ICML '05, 2005.
-
(2005)
ICML '05
-
-
Yu, K.1
Tresp, V.2
Schwaighofer, A.3
-
23
-
-
55149096818
-
Flexible latent variable models for multi-task learning
-
J. Zhang, Z. Ghahramani, and Y. Yang. Flexible latent variable models for multi-task learning. Mach. Learn., 73(3):221-242, 2008.
-
(2008)
Mach. Learn.
, vol.73
, Issue.3
, pp. 221-242
-
-
Zhang, J.1
Ghahramani, Z.2
Yang, Y.3
-
24
-
-
79951845184
-
Learning multiple related tasks using latent independent component analysis
-
J. Zhang, J. Zhang, Y. Yang, Z. Ghahramani, and Y. Yang. Learning multiple related tasks using latent independent component analysis. In NIPS '05, 2005.
-
(2005)
NIPS '05
-
-
Zhang, J.1
Zhang, J.2
Yang, Y.3
Ghahramani, Z.4
Yang, Y.5
|