-
1
-
-
32044458124
-
An algorithm for semi-supervised learning in image retrieval
-
K. Lu, J. Zhao, and D. Cai An algorithm for semi-supervised learning in image retrieval Pattern Recognit. 39 4 2006 717 720
-
(2006)
Pattern Recognit.
, vol.39
, Issue.4
, pp. 717-720
-
-
Lu, K.1
Zhao, J.2
Cai, D.3
-
2
-
-
67649880294
-
Semi-supervised bilinear subspace learning
-
D. Xu, and S. Yan Semi-supervised bilinear subspace learning IEEE Trans. Image Process. 18 7 2009 1671 1676
-
(2009)
IEEE Trans. Image Process.
, vol.18
, Issue.7
, pp. 1671-1676
-
-
Xu, D.1
Yan, S.2
-
3
-
-
77949723232
-
Combining context, consistency, and diversity cues for interactive image categorization
-
Z. Lu, and H. Ip Combining context, consistency, and diversity cues for interactive image categorization IEEE Trans. Multimed. 12 3 2010 194 203
-
(2010)
IEEE Trans. Multimed.
, vol.12
, Issue.3
, pp. 194-203
-
-
Lu, Z.1
Ip, H.2
-
4
-
-
77955655063
-
Semi-supervised learning in gigantic image collections
-
R. Fergus, Y. Weiss, A. Torralba, Semi-supervised learning in gigantic image collections, in: Advances in Neural Information Processing Systems, vol. 22, 2010, pp. 522-530.
-
(2010)
Advances in Neural Information Processing Systems
, vol.22
, pp. 522-530
-
-
Fergus, R.1
Weiss, Y.2
Torralba, A.3
-
5
-
-
72449199441
-
Inferring semantic concepts from community-contributed images and noisy tags
-
J. Tang, S. Yan, R. Hong, G.-J. Qi, T.-S. Chua, Inferring semantic concepts from community-contributed images and noisy tags, in: Proceedings of ACM Multimedia, 2009, pp. 223-232.
-
(2009)
Proceedings of ACM Multimedia
, pp. 223-232
-
-
Tang, J.1
Yan, S.2
Hong, R.3
Qi, G.-J.4
Chua, T.-S.5
-
6
-
-
53549116749
-
Image annotation via graph learning
-
J. Liu, M. Li, Q. Liu, H. Lu, and S. Ma Image annotation via graph learning Pattern Recognit. 42 2 2009 218 228
-
(2009)
Pattern Recognit.
, vol.42
, Issue.2
, pp. 218-228
-
-
Liu, J.1
Li, M.2
Liu, Q.3
Lu, H.4
Ma, S.5
-
7
-
-
0031620208
-
Combining labeled and unlabeled data with co-training
-
A. Blum, T. Mitchell, Combining labeled and unlabeled data with co-training, in: Proceedings of COLT, 1998.
-
(1998)
Proceedings of COLT
-
-
Blum, A.1
Mitchell, T.2
-
8
-
-
1942484430
-
Semi-supervised learning using Gaussian fields and harmonic functions
-
X. Zhu, Z. Ghahramani, J. Lafferty, Semi-supervised learning using Gaussian fields and harmonic functions, in: Proceedings of ICML, 2003, pp. 912-919.
-
(2003)
Proceedings of ICML
, pp. 912-919
-
-
Zhu, X.1
Ghahramani, Z.2
Lafferty, J.3
-
9
-
-
84899006908
-
Learning with local and global consistency
-
D. Zhou, O. Bousquet, T. Lal, J. Weston, B. Schölkopf, Learning with local and global consistency, in: Advances in Neural Information Processing Systems, vol. 16, 2004, pp. 321-328.
-
(2004)
Advances in Neural Information Processing Systems
, vol.16
, pp. 321-328
-
-
Zhou, D.1
-
10
-
-
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 48 2006 2399 2434
-
(2006)
J. Mach. Learn. Res.
, vol.7
, Issue.48
, pp. 2399-2434
-
-
Belkin, M.1
Niyogi, P.2
Sindhwani, V.3
-
11
-
-
36648998944
-
Label propagation through linear neighborhoods
-
F. Wang, and C. Zhang Label propagation through linear neighborhoods IEEE Trans. Knowl. Data Eng. 20 1 2008 55 67
-
(2008)
IEEE Trans. Knowl. Data Eng.
, vol.20
, Issue.1
, pp. 55-67
-
-
Wang, F.1
Zhang, C.2
-
12
-
-
77249095854
-
Semi-supervised learning by sparse representation
-
S. Yan, H. Wang, Semi-supervised learning by sparse representation, in: Proceedings of SDM, 2009, pp. 792-801.
-
(2009)
Proceedings of SDM
, pp. 792-801
-
-
Yan, S.1
Wang, H.2
-
14
-
-
77956555216
-
Large graph construction for scalable semi-supervised learning
-
W. Liu, J. He, S.-F. Chang, Large graph construction for scalable semi-supervised learning, in: Proceedings of ICML, 2010, pp. 679-686.
-
(2010)
Proceedings of ICML
, pp. 679-686
-
-
Liu, W.1
He, J.2
Chang, S.-F.3
-
15
-
-
78649330593
-
Efficient region-aware large graph construction towards scalable multi-label propagation
-
B.-K. Bao, B. Ni, Y. Mu, and S. Yan Efficient region-aware large graph construction towards scalable multi-label propagation Pattern Recognit. 44 3 2011 598 606
-
(2011)
Pattern Recognit.
, vol.44
, Issue.3
, pp. 598-606
-
-
Bao, B.-K.1
Ni, B.2
Mu, Y.3
Yan, S.4
-
16
-
-
84866660023
-
Non-negative low rank and sparse graph for semi-supervised learning
-
L. Zhuang, H. Gao, Z. Lin, Y. Ma, X. Zhang, N. Yu, Non-negative low rank and sparse graph for semi-supervised learning, in: Proceedings of CVPR, 2012, pp. 2328-2335.
-
(2012)
Proceedings of CVPR
, pp. 2328-2335
-
-
Zhuang, L.1
Gao, H.2
Lin, Z.3
Ma, Y.4
Zhang, X.5
Yu, N.6
-
17
-
-
84885841484
-
Manifold-preserving graph reduction for sparse semi-supervised learning
-
S. Sun, Z. Hussain, and J. Shawe-Taylor Manifold-preserving graph reduction for sparse semi-supervised learning Neurocomputing 124 2014 13 21
-
(2014)
Neurocomputing
, vol.124
, pp. 13-21
-
-
Sun, S.1
Hussain, Z.2
Shawe-Taylor, J.3
-
18
-
-
34547964043
-
Learning on graph with Laplacian regularization
-
R. Ando, T. Zhang, Learning on graph with Laplacian regularization, in: Advances in Neural Information Processing Systems, vol. 19, 2007, pp. 25-32.
-
(2007)
Advances in Neural Information Processing Systems
, vol.19
, pp. 25-32
-
-
Ando, R.1
Zhang, T.2
-
19
-
-
84878727865
-
Exhaustive and efficient constraint propagation a graph-based learning approach and its applications
-
Z. Lu, and Y. Peng Exhaustive and efficient constraint propagation a graph-based learning approach and its applications Int. J. Comput. Vis. 103 3 2013 306 325
-
(2013)
Int. J. Comput. Vis.
, vol.103
, Issue.3
, pp. 306-325
-
-
Lu, Z.1
Peng, Y.2
-
20
-
-
33751379736
-
Image denoising via sparse and redundant representations over learned dictionaries
-
M. Elad, and M. Aharon Image denoising via sparse and redundant representations over learned dictionaries IEEE Trans. Image Process. 15 12 2006 3736 3745
-
(2006)
IEEE Trans. Image Process.
, vol.15
, Issue.12
, pp. 3736-3745
-
-
Elad, M.1
Aharon, M.2
-
21
-
-
39149089704
-
Sparse representation for color image restoration
-
J. Mairal, M. Elad, and G. Sapiro Sparse representation for color image restoration IEEE Trans. Image Process. 17 1 2008 53 69
-
(2008)
IEEE Trans. Image Process.
, vol.17
, Issue.1
, pp. 53-69
-
-
Mairal, J.1
Elad, M.2
Sapiro, G.3
-
22
-
-
61549128441
-
Robust face recognition via sparse representation
-
J. Wright, A. Yang, A. Ganesh, S. Sastry, and Y. Ma Robust face recognition via sparse representation IEEE Trans. Pattern Anal. Mach. Intell. 31 2 2009 210 227
-
(2009)
IEEE Trans. Pattern Anal. Mach. Intell.
, vol.31
, Issue.2
, pp. 210-227
-
-
Wright, J.1
Yang, A.2
Ganesh, A.3
Sastry, S.4
Ma, Y.5
-
24
-
-
85014561619
-
A fast iterative shrinkage-thresholding algorithm for linear inverse problems
-
A. Beck, and M. Teboulle A fast iterative shrinkage-thresholding algorithm for linear inverse problems SIAM J. Imaging Sci. 2 1 2009 183 202
-
(2009)
SIAM J. Imaging Sci.
, vol.2
, Issue.1
, pp. 183-202
-
-
Beck, A.1
Teboulle, M.2
-
25
-
-
33646365077
-
1-norm solution is also the sparsest solution
-
1-norm solution is also the sparsest solution Commun. Pure Appl. Math. 59 7 2004 797 829
-
(2004)
Commun. Pure Appl. Math.
, vol.59
, Issue.7
, pp. 797-829
-
-
Donoho, D.1
-
26
-
-
0034215549
-
A new approach to variable selection in least squares problems
-
M. Osborne, B. Presnell, and B. Turlach A new approach to variable selection in least squares problems IMA J. Numer. Anal. 20 3 2000 389 403
-
(2000)
IMA J. Numer. Anal.
, vol.20
, Issue.3
, pp. 389-403
-
-
Osborne, M.1
Presnell, B.2
Turlach, B.3
-
27
-
-
39449126969
-
Gradient projection for sparse reconstruction application to compressed sensing and other inverse problems
-
M. Figueiredo, R. Nowak, and S. Wright Gradient projection for sparse reconstruction application to compressed sensing and other inverse problems IEEE J. Sel. Top. Signal Process. 1 4 2007 586 597
-
(2007)
IEEE J. Sel. Top. Signal Process.
, vol.1
, Issue.4
, pp. 586-597
-
-
Figueiredo, M.1
Nowak, R.2
Wright, S.3
-
28
-
-
84864036295
-
Efficient sparse coding algorithms
-
H. Lee, A. Battle, R. Raina, A. Ng, Efficient sparse coding algorithms, in: Advances in Neural Information Processing Systems, vol. 19, 2007, pp. 801-808.
-
(2007)
Advances in Neural Information Processing Systems
, vol.19
, pp. 801-808
-
-
Lee, H.1
Battle, A.2
Raina, R.3
Ng, A.4
-
29
-
-
85194972808
-
Regression shrinkage and selection via the Lasso
-
R. Tibshirani Regression shrinkage and selection via the Lasso J. R. Stat. Soc. Ser. B 58 1 1996 267 288
-
(1996)
J. R. Stat. Soc. Ser. B
, vol.58
, Issue.1
, pp. 267-288
-
-
Tibshirani, R.1
-
30
-
-
77955405900
-
Feature selection guided by structural information
-
M. Slawski, W. zu Castell, and G. Tutz Feature selection guided by structural information Ann. Appl. Stat. 4 2 2010 1056 1080
-
(2010)
Ann. Appl. Stat.
, vol.4
, Issue.2
, pp. 1056-1080
-
-
Slawski, M.1
Zu Castell, W.2
Tutz, G.3
-
31
-
-
84874031618
-
Heterogeneous constraint propagation with constrained sparse representation
-
Z. Lu, Y. Peng, Heterogeneous constraint propagation with constrained sparse representation, in: Proceedings of ICDM, 2012, pp. 1002-1007.
-
(2012)
Proceedings of ICDM
, pp. 1002-1007
-
-
Lu, Z.1
Peng, Y.2
-
32
-
-
79955855934
-
Laplacian support vector machines trained in the primal
-
S. Melacci, and M. Belkin Laplacian support vector machines trained in the primal J. Mach. Learn. Res. 12 2011 1149 1184
-
(2011)
J. Mach. Learn. Res.
, vol.12
, pp. 1149-1184
-
-
Melacci, S.1
Belkin, M.2
-
33
-
-
56449125402
-
Large scale manifold transduction
-
M. Karlen, J. Weston, A. Erkan, R. Collobert, Large scale manifold transduction, in: Proceedings of ICML, 2008, pp. 448-455.
-
(2008)
Proceedings of ICML
, pp. 448-455
-
-
Karlen, M.1
Weston, J.2
Erkan, A.3
Collobert, R.4
-
34
-
-
78649409198
-
Sparse semi-supervised learning using conjugate functions
-
S. Sun, and J. Shawe-Taylor Sparse semi-supervised learning using conjugate functions J. Mach. Learn. Res. 11 2010 2423 2455
-
(2010)
J. Mach. Learn. Res.
, vol.11
, pp. 2423-2455
-
-
Sun, S.1
Shawe-Taylor, J.2
-
35
-
-
84881061407
-
A second order cone programming approach for semi-supervised learning
-
G. Huang, S. Song, J.N. Gupta, and C. Wu A second order cone programming approach for semi-supervised learning Pattern Recognit. 46 12 2013 3548 3558
-
(2013)
Pattern Recognit.
, vol.46
, Issue.12
, pp. 3548-3558
-
-
Huang, G.1
Song, S.2
Gupta, J.N.3
Wu, C.4
-
36
-
-
84897560409
-
Label propagation through minimax paths for scalable semi-supervised learning
-
K.-H. Kim, and S. Choi Label propagation through minimax paths for scalable semi-supervised learning Pattern Recognit. Lett. 45 2014 17 25
-
(2014)
Pattern Recognit. Lett.
, vol.45
, pp. 17-25
-
-
Kim, K.-H.1
Choi, S.2
-
37
-
-
84893674326
-
Kernel-based transition probability toward similarity measure for semi-supervised learning
-
T. Kobayashi Kernel-based transition probability toward similarity measure for semi-supervised learning Pattern Recognit. 47 5 2014 1994 2010
-
(2014)
Pattern Recognit.
, vol.47
, Issue.5
, pp. 1994-2010
-
-
Kobayashi, T.1
-
38
-
-
78149362519
-
Semi-supervised learning using sparse eigenfunction bases
-
K. Sinha, M. Belkin, Semi-supervised learning using sparse eigenfunction bases, in: Advances in Neural Information Processing Systems, vol. 22, 2010, pp. 1687-1695.
-
(2010)
Advances in Neural Information Processing Systems
, vol.22
, pp. 1687-1695
-
-
Sinha, K.1
Belkin, M.2
-
39
-
-
77955994285
-
Local features are not lonely - Laplacian sparse coding for image classification
-
S. Gao, I. Tsang, L.-T. Chia, P. Zhao, Local features are not lonely - Laplacian sparse coding for image classification, in: Proceedings of CVPR, 2010, pp. 3555-3561.
-
(2010)
Proceedings of CVPR
, pp. 3555-3561
-
-
Gao, S.1
Tsang, I.2
Chia, L.-T.3
Zhao, P.4
-
40
-
-
80053139009
-
Smoothing proximal gradient method for general structured sparse learning
-
X. Chen, Q. Lin, S. Kim, J.G. Carbonell, E.P. Xing, Smoothing proximal gradient method for general structured sparse learning, in: Proceedings of UAI, 2011, pp. 105-114.
-
(2011)
Proceedings of UAI
, pp. 105-114
-
-
Chen, X.1
Lin, Q.2
Kim, S.3
Carbonell, J.G.4
Xing, E.P.5
-
41
-
-
84867114870
-
Pairwise fused Lasso
-
Department of Statistics, University of Munich
-
S. Petry, C. Flexeder, G. Tutz, Pairwise fused Lasso, Technical Report 102, Department of Statistics, University of Munich, 2011.
-
(2011)
Technical Report 102
-
-
Petry, S.1
Flexeder, C.2
Tutz, G.3
-
42
-
-
27244449175
-
Regularization on discrete spaces
-
D. Zhou, B. Scholköpf, Regularization on discrete spaces, in: Proceedings of DAGM, 2005, pp. 361-368.
-
(2005)
Proceedings of DAGM
, pp. 361-368
-
-
Zhou, D.1
-
43
-
-
80054063086
-
Learning compressible models
-
Y. Zhang, J.G. Schneider, A. Dubrawski, Learning compressible models, in: Proceedings of SDM, 2010, pp. 872-881.
-
(2010)
Proceedings of SDM
, pp. 872-881
-
-
Zhang, Y.1
Schneider, J.G.2
Dubrawski, A.3
-
46
-
-
56449131204
-
An RKHS for multi-view learning and manifold coregularization
-
V. Sindhwani, D. Rosenberg, An RKHS for multi-view learning and manifold coregularization, in: Proceedings of ICML, 2008, pp. 976-983.
-
(2008)
Proceedings of ICML
, pp. 976-983
-
-
Sindhwani, V.1
Rosenberg, D.2
-
47
-
-
79960700643
-
Spatial Markov kernels for image categorization and annotation
-
Z. Lu, and H. Ip Spatial Markov kernels for image categorization and annotation IEEE Trans. Syst. Man Cybern. Part B 41 4 2011 976 989
-
(2011)
IEEE Trans. Syst. Man Cybern. Part B
, vol.41
, Issue.4
, pp. 976-989
-
-
Lu, Z.1
Ip, H.2
-
48
-
-
51949086172
-
Semi-supervised classification by low density separation
-
O. Chapelle, A. Zien, Semi-supervised classification by low density separation, in: Proceedings of AISTATS, 2005, pp. 57-64.
-
(2005)
Proceedings of AISTATS
, pp. 57-64
-
-
Chapelle, O.1
Zien, A.2
|