-
2
-
-
27844439373
-
A framework for learning predictive structures from multiple tasks and unlabeled data
-
Ando, R. K. And Zhang, T. 2005. A Framework For Learning Predictive Structures From Multiple Tasks And Unlabeled Data. J. Mach. Learn. Res. 6, 1817-1853.
-
(2005)
J. Mach. Learn. Res
, vol.6
, pp. 1817-1853
-
-
Ando, R.1
Zhang, T.2
-
3
-
-
84864063089
-
Multi-task feature learning
-
Argyriou, A., Evgeniou, T., And Pontil, M. 2006. Multi-Task Feature Learning. Adv. Neural Inf. Process. Syst. 19, 41-48.
-
(2006)
Adv. Neural Inf. Process. Syst
, vol.19
, pp. 41-48
-
-
Argyriou, A.1
Evgeniou, T.2
Pontil, M.3
-
4
-
-
55149088329
-
Convex multi-task feature learning
-
Argyriou, A., Evgeniou, T., And Pontil, M. 2008. Convex Multi-Task Feature Learning. Mach. Learn. 73, 3, 243-272.
-
(2008)
Mach. Learn
, vol.73
, Issue.3
, pp. 243-272
-
-
Argyriou, A.1
Evgeniou, T.2
Pontil, M.3
-
5
-
-
74549145018
-
Multi-task learning for learning to rank in web search
-
Bai, J., Zhou, K., Xue, G.-R., Zha, H., Sun, G., Tseng, B. L., Zheng, Z., And Chang, Y. 2009. Multi-Task Learning For Learning To Rank In Web Search. In Proceedings Of The 18Th Acm Conference On Information And Knowledge Management (Cikm'09). 1549-1552.
-
(2009)
Proceedings Of The 18Th Acm Conference On Information And Knowledge Management (Cikm'09).
, pp. 1549-1552
-
-
Bai, J.1
Zhou, K.2
Xue, G.-R.3
Zha, H.4
Sun, G.5
Tseng, B.L.6
Zheng, Z.7
Chang, Y.8
-
6
-
-
0346238931
-
Task clustering and gating for bayesian multitask learning
-
Bakker, B. And Heskes, T. 2003. Task Clustering And Gating For Bayesian Multitask Learning. J. Mach. Learn. Res. 4, 83-99.
-
(2003)
J. Mach. Learn. Res
, vol.4
, pp. 83-99
-
-
Bakker, B.1
Heskes, T.2
-
7
-
-
41549108812
-
Algorithms for sparse linear classifiers in the massive data setting
-
Balakrishnan, S. And Madigan, D. 2008. Algorithms For Sparse Linear Classifiers In The Massive Data Setting. J. Mach. Learn. Res. 9, 313-337. (Pubitemid 351469019)
-
(2008)
Journal of Machine Learning Research
, vol.9
, pp. 313-337
-
-
Balakrishnan, S.1
Madigan, D.2
-
8
-
-
55149085224
-
A notion of task relatedness yielding provable multiple-task learning guarantees
-
Ben-David, S. And Borbely, R. S. 2008. A Notion Of Task Relatedness Yielding Provable Multiple-Task Learning Guarantees. Mach. Learn. 73, 3, 273-287.
-
(2008)
Mach. Learn
, vol.73
, Issue.3
, pp. 273-287
-
-
Ben-David, S.1
Borbely, R.S.2
-
9
-
-
9444270330
-
Exploiting Task Relatedness for Multiple Task Learning
-
Learning Theory and Kernel Machines
-
Ben-David, S. And Schuller, R. 2003. Exploiting Task Relatedness For Mulitple Task Learning. In Proceedings Of The 16Th Annual Conference On Learning Theory (Colt'03). 567-580. (Pubitemid 37053230)
-
(2003)
Lecture Notes In Computer Science
, Issue.2777
, pp. 567-580
-
-
Ben-David, S.1
Schuller, R.2
-
11
-
-
0031189914
-
Multitask Learning
-
Caruana, R. 1997. Multitask Learning. Mach. Learn. 28, 1, 41-75. (Pubitemid 127507169)
-
(1997)
Machine Learning
, vol.28
, Issue.1
, pp. 41-75
-
-
Caruana, R.1
-
13
-
-
84863232691
-
Learning incoherent sparse and low-rank patterns from multiple tasks
-
Chen, J., Liu, J., And Ye, J. 2012. Learning Incoherent Sparse And Low-Rank Patterns From Multiple Tasks. Acm Trans. Knowl. Discov. Data 5, 4.
-
(2012)
Acm Trans. Knowl. Discov. Data 5
, vol.4
-
-
Chen, J.1
Liu, J.2
Ye, J.3
-
14
-
-
71149094644
-
A convex formulation for learning shared structures from multiple tasks
-
Chen, J.,Tang, L.,Liu, J., And Ye, J. 2009A. A Convex Formulation For Learning Shared Structures From Multiple Tasks. In Proceedings Of The 26Th Annual International Conference On Machine Learning (Icml'09). 18.
-
(2009)
Proceedings Of The 26Th Annual International Conference On Machine Learning (Icml'09).
, vol.18
-
-
Chen, J.1
Tang, L.2
Liu, J.3
Ye, J.4
-
15
-
-
77951173993
-
Accelerated gradient method for multi-task sparse learning problem
-
Chen, X., Pan, W.,Kwok, J. T., And Carbonell, J. G. 2009B. Accelerated Gradient Method For Multi-Task Sparse Learning Problem. In Proceedings Of The 9Th Ieee International Conference On Data Mining (Icdm'09). 746-751.
-
(2009)
Proceedings Of The 9Th Ieee International Conference On Data Mining (Icdm'09).
, pp. 746-751
-
-
Chen, X.1
Pan, W.2
Kwok, J.T.3
Carbonell, J.G.4
-
16
-
-
33746070785
-
Online multitask learning
-
Learning Theory - 19th Annual Conference on Learning Theory, COLT 2006, Proceedings
-
Dekel, O., Long, P. M., And Singer, Y. 2006. Online Multitask Learning. In Proceedings Of The 19Th Annual Conference On Learning Theory (Colt'06). 453-467. (Pubitemid 44072212)
-
(2006)
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
, vol.4005 LNAI
, pp. 453-467
-
-
Dekel, O.1
Long, P.M.2
Singer, Y.3
-
17
-
-
79952724800
-
Minimum description length penalization for group and multi-task sparse learning
-
Dhillon, P. S., Foster, D. P., And Ungar, L. H. 2011. Minimum Description Length Penalization For Group And Multi-Task Sparse Learning. J. Mach. Learn. Res. 12, 525-564.
-
(2011)
J. Mach. Learn. Res
, vol.12
, pp. 525-564
-
-
Dhillon, P.S.1
Foster, D.P.2
Ungar, L.H.3
-
18
-
-
70350625031
-
Multi-task feature selection using the multiple inclusion criterion (mic)
-
Dhillon, P. S., Tomasik, B., Foster, D. P., And Ungar, L. H. 2009. Multi-Task Feature Selection Using The Multiple Inclusion Criterion (Mic). In Proceedings Of The European Conference On Machine Learning And Knowledge Discovery In Databases (Ecml/Pkdd'09). 276-289.
-
(2009)
Proceedings Of The European Conference On Machine Learning And Knowledge Discovery In Databases (Ecml/Pkdd'09).
, pp. 276-289
-
-
Dhillon, P.S.1
Tomasik, B.2
Foster, D.P.3
Ungar, L.H.4
-
19
-
-
78651271942
-
Efficient learning using forward-backward splitting
-
Duchi, J. And Singer, Y. 2009. Efficient Learning Using Forward-Backward Splitting. J. Mach. Learn. Res. 10, 2873-2898.
-
(2009)
J. Mach. Learn. Res
, vol.10
, pp. 2873-2898
-
-
Duchi, J.1
Singer, Y.2
-
20
-
-
21844456299
-
Learning multiple tasks with kernel methods
-
Evgeniou, T.,Micchelli, C. A., And Pontil, M. 2005. Learning Multiple Tasks With Kernel Methods. J. Mach. Learn. Res. 6, 615-637.
-
(2005)
J. Mach. Learn. Res
, vol.6
, pp. 615-637
-
-
Evgeniou, T.1
Micchelli, C.A.2
Pontil, M.3
-
24
-
-
77958542913
-
Multi-task sparse discriminant analysis (mtsda) with overlapping categories
-
Han, Y., Wu, F., Jia, J., Zhuang, Y., And Yu, B. 2010. Multi-Task Sparse Discriminant Analysis (Mtsda) With Overlapping Categories. In Proceedings Of The 24Th Aaai Conference On Artificial Intelligence.
-
(2010)
Proceedings Of The 24Th Aaai Conference On Artificial Intelligence
-
-
Han, Y.1
Wu, F.2
Jia, J.3
Zhuang, Y.4
Yu, B.5
-
25
-
-
35348918820
-
Logarithmic regret algorithms for online convex optimization
-
DOI 10.1007/s10994-007-5016-8, Special Issue on COLT 2006; Guest Editors: Avrim Blum, Gabor Lugosi and Hans Ulrich Simon
-
Hazan, E., Agarwal, A., And Kale, S. 2007. Logarithmic Regret Algorithms For Online Convex Optimization. Mach. Learn. 69, 2-3, 169-192. (Pubitemid 47574314)
-
(2007)
Machine Learning
, vol.69
, Issue.2-3
, pp. 169-192
-
-
Hazan, E.1
Agarwal, A.2
Kale, S.3
-
26
-
-
77956508892
-
Accelerated gradient methods for stochastic optimization and online learning
-
Hu, C., Kwok, J., And Pan, W. 2009. Accelerated Gradient Methods For Stochastic Optimization And Online Learning. Adv. Neural Inf. Process. Syst. 22, 781-789.
-
(2009)
Adv. Neural Inf. Process. Syst
, vol.22
, pp. 781-789
-
-
Hu, C.1
Kwok, J.2
Pan, W.3
-
28
-
-
79551660140
-
Multitask sparsity via maximum entropy discrimination
-
Jebara, T. 2011. Multitask Sparsity Via Maximum Entropy Discrimination. J. Mach. Learn. Res. 12, 75-110.
-
(2011)
J. Mach. Learn. Res
, vol.12
, pp. 75-110
-
-
Jebara, T.1
-
29
-
-
64149115569
-
Sparse online learning via truncated gradient
-
Langford, J., Li, L., And Zhang, T. 2009. Sparse Online Learning Via Truncated Gradient. J. Mach. Learn. Res. 10, 777-801.
-
(2009)
J. Mach. Learn. Res
, vol.10
, pp. 777-801
-
-
Langford, J.1
Li, L.2
Zhang, T.3
-
30
-
-
0030521288
-
Hierarchical bayes conjoint analysis: Recovery of partworth heterogeneity from reduced experimental designs
-
Lenk, P. J.,Desarbo,W. S., Green, P. E., And Young, M. R. 1996. Hierarchical Bayes Conjoint Analysis: Recovery Of Partworth Heterogeneity From Reduced Experimental Designs. Market. Sci. 15, 2, 173-191.
-
(1996)
Market. Sci
, vol.15
, Issue.2
, pp. 173-191
-
-
Lenk, P.1
Desarbo, W.2
Green, P.E.3
Young, M.R.4
-
31
-
-
84865078183
-
Online learning for collaborative filtering
-
Ling, G., Yang, H., King, I., And Lyu, M. R. 2012. Online Learning For Collaborative Filtering. In Proceedings Of The Ieee World Congress On Computational Intelligence (Wcci'12). 1-8.
-
(2012)
Proceedings Of The Ieee World Congress On Computational Intelligence (Wcci'12).
, pp. 1-8
-
-
Ling, G.1
Yang, H.2
King, I.3
Lyu, M.R.4
-
32
-
-
71149111015
-
Blockwise coordinate descent procedures for the multi-task lasso, with applications to neural semantic basis discovery
-
Liu, H., Palatucci, M., And Zhang, J. 2009A. Blockwise Coordinate Descent Procedures For The Multi-Task Lasso, With Applications To Neural Semantic Basis Discovery. In Proceedings Of The 26Th Annual International Conference On Machine Learning (Icml'09). 649-656.
-
(2009)
Proceedings Of The 26Th Annual International Conference On Machine Learning (Icml'09).
, pp. 649-656
-
-
Liu, H.1
Palatucci, M.2
Zhang, J.3
-
36
-
-
65249121279
-
Primal-dual subgradient methods for convex problems
-
Nesterov, Y. 2009. Primal-Dual Subgradient Methods For Convex Problems. Math. Program. 120, 1, 221-259.
-
(2009)
Math. Program
, vol.120
, Issue.1
, pp. 221-259
-
-
Nesterov, Y.1
-
37
-
-
77953322499
-
Joint covariate selection and joint subspace selection for multiple classification problems
-
Obozinski, G., Taskar, B., And Jordan, M. I. 2009. Joint Covariate Selection And Joint Subspace Selection For Multiple Classification Problems. Statist. Comput. 20, 2, 231-252.
-
(2009)
Statist. Comput
, vol.20
, Issue.2
, pp. 231-252
-
-
Obozinski, G.1
Taskar, B.2
Jordan, M.I.3
-
38
-
-
79251515185
-
Trace norm regularization: Reformulations, algorithms, and multi-task learning
-
Pong, T. K., Tseng, P., Ji, S., And Ye, J. 2010. Trace Norm Regularization: Reformulations, Algorithms, And Multi-Task Learning. Siam J. Optim. 20, 6, 3465-3489.
-
(2010)
Siam J. Optim.
, vol.20
, Issue.6
, pp. 3465-3489
-
-
Pong, T.K.1
Tseng, P.2
Ji, S.3
Ye, J.4
-
39
-
-
71149088514
-
An efficient projection for l1,8 regularization
-
Quattoni, A., Carreras, X., Collins, M., And Darrell, T. 2009. An Efficient Projection For L1,8 Regularization. In Proceedings Of The 26Th International Conference On Machine Learning (Icml'09), 857-864.
-
(2009)
Proceedings Of The 26Th International Conference On Machine Learning (Icml'09
, pp. 857-864
-
-
Quattoni, A.1
Carreras, X.2
Collins, M.3
Darrell, T.4
-
40
-
-
35348915372
-
A primal-dual perspective of online learning algorithms
-
DOI 10.1007/s10994-007-5014-x, Special Issue on COLT 2006; Guest Editors: Avrim Blum, Gabor Lugosi and Hans Ulrich Simon
-
Shalev-Shwartz, S. And Singer, Y. 2007. A Primal-Dual Perspective Of Online Learning Algorithms. Mach. Learn. 69, 2-3, 115-142. (Pubitemid 47574312)
-
(2007)
Machine Learning
, vol.69
, Issue.2-3
, pp. 115-142
-
-
Shalev-Shwartz, S.1
Singer, Y.2
-
42
-
-
85194972808
-
Regression shrinkage and selection via the lasso
-
Tibshirani, R. 1996. Regression Shrinkage And Selection Via The Lasso. J. Roy. Statist. Soc. B58, 1, 267-288.
-
(1996)
J. Roy. Statist. Soc. B58
, vol.1
, pp. 267-288
-
-
Tibshirani, R.1
-
44
-
-
78649396336
-
Dual averaging method for regularized stochastic learning and online optimization
-
Xiao, L. 2010. Dual Averaging Method For Regularized Stochastic Learning And Online Optimization. J. Mach. Learn. Res. 11, 2543-2596.
-
(2010)
J. Mach. Learn. Res
, vol.11
, pp. 2543-2596
-
-
Xiao, L.1
-
45
-
-
77956547440
-
Simple and efficient multiple kernel learning by group lasso
-
Xu, Z., Jin, R., Yang, H.,King, I., And Lyu, M. R. 2010. Simple And Efficient Multiple Kernel Learning By Group Lasso. In Proceedings Of The 27Th International Conference On Machine Learning (Icml'10). 1175-1182.
-
(2010)
Proceedings Of The 27Th International Conference On Machine Learning (Icml'10).
, pp. 1175-1182
-
-
Xu, Z.1
Jin, R.2
Yang H.King, I.3
Lyu, M.R.4
-
49
-
-
77956496396
-
Online learning for group lasso
-
Yang, H., Xu, Z., King, I., And Lyu, M. R. 2010C. Online Learning For Group Lasso. In Proceedings Of The 27Th International Conference On Machine Learning (Icml'10). 1191-1198.
-
(2010)
Proceedings Of The 27Th International Conference On Machine Learning (Icml'10).
, pp. 1191-1198
-
-
Yang, H.1
Xu, Z.2
King, I.3
Lyu, M.R.4
-
50
-
-
79952183228
-
Efficient sparse generalized multiple kernel learning
-
Yang, H., Xu, Z., Ye, J., King, I., And Lyu, M. R. 2011B. Efficient Sparse Generalized Multiple Kernel Learning. Ieee Trans. Neural Netw. 22, 3, 433-446.
-
(2011)
Ieee Trans. Neural Netw.
, vol.22
, Issue.3
, pp. 433-446
-
-
Yang, H.1
Xu, Z.2
Ye, J.3
King, I.4
Lyu, M.R.5
-
52
-
-
85162027638
-
Probabilistic multi-task feature selection
-
Zhang, Y., Yeung, D.-Y., And Xu, Q. 2010. Probabilistic Multi-Task Feature Selection. Adv. Neural Inf. Process. Syst. 23, 2559-2567.
-
(2010)
Adv. Neural Inf. Process. Syst
, vol.23
, pp. 2559-2567
-
-
Zhang, Y.1
Yeung, D.-Y.2
Xu, Q.3
-
53
-
-
79960148547
-
Double updating online learning
-
Zhao, P., Hoi, S. C. H., And Jin, R. 2011A. Double Updating Online Learning. J. Mach. Learn. Res. 12, 1587-1615.
-
(2011)
J. Mach. Learn. Res
, vol.12
, pp. 1587-1615
-
-
Zhao, P.1
Hoi, S.C.H.2
Jin, R.3
-
54
-
-
80053451407
-
Online auc maximization
-
Zhao, P., Hoi, S. C. H., Jin, R., And Yang, T. 2011B. Online Auc Maximization. In Proceedings Of The 28Th International Conference On Machine Learning (Icml'11). 233-240.
-
(2011)
Proceedings Of The 28Th International Conference On Machine Learning (Icml'11).
, pp. 233-240
-
-
Zhao, P.1
Hoi, S.C.H.2
Jin, R.3
Yang, T.4
|