-
1
-
-
77950343112
-
A Discriminative Model for Semi-Supervised Learning
-
M.F. Balcan and A. Blum, "A Discriminative Model for Semi-Supervised Learning," J. ACM, vol. 57, no. 3, article 19, 2010.
-
(2010)
J. ACM
, vol.57
, Issue.3
-
-
Balcan, M.F.1
Blum, A.2
-
2
-
-
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. Machine Learning Research, vol. 7, pp. 2399-2434, 2006.
-
(2006)
J. Machine Learning Research
, vol.7
, pp. 2399-2434
-
-
Belkin, M.1
Niyogi, P.2
Sindhwani, V.3
-
3
-
-
77956501439
-
Does Unlabeled Data Provably Help? Worst-Case Analysis of the Sample Complexity of Semi-Supervised Learning
-
S. Ben David, T. Lu, and D. Pál, "Does Unlabeled Data Provably Help? Worst-Case Analysis of the Sample Complexity of Semi-Supervised Learning," Proc. 21st Ann. Conf. Learning Theory, pp. 33-44, 2008.
-
(2008)
Proc. 21st Ann. Conf. Learning Theory
, pp. 33-44
-
-
David, S.B.1
Lu, T.2
Pál, D.3
-
5
-
-
11144352445
-
Convergence of Alternating Optimization
-
J.C. Bezdek and R.J. Hathaway, "Convergence of Alternating Optimization," Neural, Parallel & Scientific Computations, vol. 11, no. 4, pp. 351-368, 2003.
-
(2003)
Neural, Parallel & Scientific Computations
, vol.11
, Issue.4
, pp. 351-368
-
-
Bezdek, J.C.1
Hathaway, R.J.2
-
9
-
-
33749257143
-
A Continuation Method for Semi-Supervised SVMs
-
O. Chapelle, M. Chi, and A. Zien, "A Continuation Method for Semi-Supervised SVMs," Proc. 23rd Int'l Conf. Machine Learning, pp. 185-192, 2006.
-
(2006)
Proc. 23rd Int'l Conf. Machine Learning
, pp. 185-192
-
-
Chapelle, O.1
Chi, M.2
Zien, A.3
-
11
-
-
41549144249
-
Optimization Techniques for Semi-Supervised Support Vector Machines
-
O. Chapelle, V. Sindhwani, and S.S. Keerthi, "Optimization Techniques for Semi-Supervised Support Vector Machines," J. Machine Learning Research, vol. 9, pp. 203-233, 2008.
-
(2008)
J. Machine Learning Research
, vol.9
, pp. 203-233
-
-
Chapelle, O.1
Sindhwani, V.2
Keerthi, S.S.3
-
13
-
-
27344454215
-
Learning from Labeled and Unlabeled Data: An Empirical Study across Techniques and Domains
-
N. Chawla and G. Karakoulas, "Learning from Labeled and Unlabeled Data: An Empirical Study across Techniques and Domains," J. Artificial Intelligence Research, vol. 23, pp. 331-366, 2005.
-
(2005)
J. Artificial Intelligence Research
, vol.23
, pp. 331-366
-
-
Chawla, N.1
Karakoulas, G.2
-
14
-
-
78649326338
-
Semi-Supervised Learning via Regularized Boosting Working on Multiple Semi-Supervised Assumptions
-
Jan.
-
K. Chen and S. Wang, "Semi-Supervised Learning via Regularized Boosting Working on Multiple Semi-Supervised Assumptions," IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 33, no. 1, pp. 129-143, Jan. 2011.
-
(2011)
IEEE Trans. Pattern Analysis and Machine Intelligence
, vol.33
, Issue.1
, pp. 129-143
-
-
Chen, K.1
Wang, S.2
-
15
-
-
33747128180
-
Large Scale Transductive SVMs
-
R. Collobert, F. Sinz, J. Weston, and L. Bottou, "Large Scale Transductive SVMs," J. Machine Learning Research, vol. 7, pp. 1687-1712, 2006.
-
(2006)
J. Machine Learning Research
, vol.7
, pp. 1687-1712
-
-
Collobert, R.1
Sinz, F.2
Weston, J.3
Bottou, L.4
-
16
-
-
1942452771
-
Semi-Supervised Learning of Mixture Models
-
F.G. Cozman, I. Cohen, and M.C. Cirelo, "Semi-Supervised Learning of Mixture Models," Proc. 20th Int'l Conf. Machine Learning, pp. 99-106, 2003.
-
(2003)
Proc. 20th Int'l Conf. Machine Learning
, pp. 99-106
-
-
Cozman, F.G.1
Cohen, I.2
Cirelo, M.C.3
-
17
-
-
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," J. Royal Statistical Soc. B, vol. 39, no. 1, pp. 1-38, 1977.
-
(1977)
J. Royal Statistical Soc. B
, vol.39
, Issue.1
, pp. 1-38
-
-
Dempster, A.P.1
Laird, N.M.2
Rubin, D.B.3
-
18
-
-
29144499905
-
Working Set Selection Using Second Order Information for Training Support Vector Machines
-
R.E. Fan, P.H. Chen, and C.J. Lin, "Working Set Selection Using Second Order Information for Training Support Vector Machines," J. Machine Learning Research, vol. 6, pp. 1889-1918, 2005.
-
(2005)
J. Machine Learning Research
, vol.6
, pp. 1889-1918
-
-
Fan, R.E.1
Chen, P.H.2
Lin, C.J.3
-
19
-
-
78049531090
-
Combining Labelled and Unlabelled Data: A Case Study on Fisher Kernels and Transductive Inference for Biological Entity Recognition
-
C. Goutte, H. Déjean, E. Gaussier, N. Cancedda, and J.M. Renders, "Combining Labelled and Unlabelled Data: A Case Study on Fisher Kernels and Transductive Inference for Biological Entity Recognition," Proc. Sixth Conf. Natural Language Learning, pp. 1-7, 2002.
-
(2002)
Proc. Sixth Conf. Natural Language Learning
, pp. 1-7
-
-
Goutte, C.1
Déjean, H.2
Gaussier, E.3
Cancedda, N.4
Renders, J.M.5
-
21
-
-
56449086680
-
A Dual Coordinate Descent Method for Large-Scale Linear SVM
-
C.J. Hsieh, K.W. Chang, C.J. Lin, S.S. Keerthi, and S. Sundararajan, "A Dual Coordinate Descent Method for Large-Scale Linear SVM," Proc. 25th Int'l Conf. Machine Learning, pp. 408-415, 2008.
-
(2008)
Proc. 25th Int'l Conf. Machine Learning
, pp. 408-415
-
-
Hsieh, C.J.1
Chang, K.W.2
Lin, C.J.3
Keerthi, S.S.4
Sundararajan, S.5
-
23
-
-
0001938951
-
Transductive Inference for Text Classification Using Support Vector Machines
-
T. Joachims, "Transductive Inference for Text Classification Using Support Vector Machines," Proc. 16th Int'l Conf. Machine Learning, pp. 200-209, 1999.
-
(1999)
Proc. 16th Int'l Conf. Machine Learning
, pp. 200-209
-
-
Joachims, T.1
-
24
-
-
8844252509
-
Transductive Support Vector Machines and Applications in Bioinformatics for Promoter Recognition
-
N. Kasabov and S. Pang, "Transductive Support Vector Machines and Applications in Bioinformatics for Promoter Recognition," Proc. Int'l Conf. Neural Networks and Signal Processing, pp. 1-6, 2003.
-
(2003)
Proc. Int'l Conf. Neural Networks and Signal Processing
, pp. 1-6
-
-
Kasabov, N.1
Pang, S.2
-
25
-
-
0343136966
-
Optimization by Simulated Annealing: Quantitative Studies
-
S. Kirkpatrick, "Optimization by Simulated Annealing: Quantitative Studies," J. Statistical Physics, vol. 34, no. 5, pp. 975-986, 1984.
-
(1984)
J. Statistical Physics
, vol.34
, Issue.5
, pp. 975-986
-
-
Kirkpatrick, S.1
-
28
-
-
71149093081
-
Semi-Supervised Learning Using Label Mean
-
Y.-F. Li, J.T. Kwok, and Z.-H. Zhou, "Semi-Supervised Learning Using Label Mean," Proc. 26th Int'l Conf. Machine learning, pp. 633-640, 2009.
-
(2009)
Proc. 26th Int'l Conf. Machine Learning
, pp. 633-640
-
-
Li, Y.-F.1
Kwok, J.T.2
Zhou, Z.-H.3
-
29
-
-
84862291617
-
Tighter and Convex Maximum Margin Clustering
-
Y.-F. Li, I.W. Tsang, J.T. Kwok, and Z.-H. Zhou, "Tighter and Convex Maximum Margin Clustering," Proc. 12th Int'l Conf. Artificial Intelligence and Statistics, pp. 344-351, 2009.
-
(2009)
Proc. 12th Int'l Conf. Artificial Intelligence and Statistics
, pp. 344-351
-
-
Li, Y.-F.1
Tsang, I.W.2
Kwok, J.T.3
Zhou, Z.-H.4
-
30
-
-
84883241774
-
Convex and Scalable Weakly Labeled SVMS
-
Y.-F. Li, I.W. Tsang, J.T. Kwok, and Z.-H. Zhou, "Convex and Scalable Weakly Labeled SVMS," J. Machine Learning Research, vol. 14, pp. 2151-2188, 2013.
-
(2013)
J. Machine Learning Research
, vol.14
, pp. 2151-2188
-
-
Li, Y.-F.1
Tsang, I.W.2
Kwok, J.T.3
Zhou, Z.-H.4
-
31
-
-
80055041497
-
Improving Semi-Supervised Support Vector Machines through Unlabeled Instances Selection
-
Y.-F. Li and Z.-H. Zhou, "Improving Semi-Supervised Support Vector Machines through Unlabeled Instances Selection," Proc. 25th AAAI Conf. Artificial Intelligence, pp. 386-391, 2011.
-
(2011)
Proc. 25th AAAI Conf. Artificial Intelligence
, pp. 386-391
-
-
Li, Y.-F.1
Zhou, Z.-H.2
-
33
-
-
77956555216
-
Large Graph Construction for Scalable Semi-Supervised Learning
-
W. Liu, J.-F. He, and S.-F. Chang, "Large Graph Construction for Scalable Semi-Supervised Learning," Proc. 27th Int'l Conf. Machine Learning, pp. 679-686, 2010.
-
(2010)
Proc. 27th Int'l Conf. Machine Learning
, pp. 679-686
-
-
Liu, W.1
He, J.-F.2
Chang, S.-F.3
-
34
-
-
84865425579
-
Robust and Scalable Graph-Based Semisupervised Learning
-
Sep.
-
W. Liu, J. Wang, and S.-F. Chang, "Robust and Scalable Graph-Based Semisupervised Learning," Proc. IEEE, vol. 100, no. 9, pp. 2624-2638, Sep. 2012.
-
(2012)
Proc. IEEE
, vol.100
, Issue.9
, pp. 2624-2638
-
-
Liu, W.1
Wang, J.2
Chang, S.-F.3
-
35
-
-
84898980291
-
A Mixture of Experts Classifier with Learning Based on Both Labelled and Unlabelled Data
-
D.J. Miller and H.S. Uyar, "A Mixture of Experts Classifier with Learning Based on Both Labelled and Unlabelled Data," Proc. Advances in Neural Information Processing Systems, vol. 9, pp. 571-577, 1997.
-
(1997)
Proc. Advances in Neural Information Processing Systems
, vol.9
, pp. 571-577
-
-
Miller, D.J.1
Uyar, H.S.2
-
36
-
-
0033886806
-
Text Classification from Labeled and Unlabeled Documents Using EM
-
K. Nigam, A.K. McCallum, S. Thrun, and T. Mitchell, "Text Classification from Labeled and Unlabeled Documents Using EM," Machine Learning, vol. 39, no. 2, pp. 103-134, 2000.
-
(2000)
Machine Learning
, vol.39
, Issue.2
, pp. 103-134
-
-
Nigam, K.1
McCallum, A.K.2
Thrun, S.3
Mitchell, T.4
-
37
-
-
33749242620
-
Deterministic Annealing for Semi-Supervised Kernel Machines
-
V. Sindhwani, S.S. Keerthi, and O. Chapelle, "Deterministic Annealing for Semi-Supervised Kernel Machines," Proc. 23rd Int'l Conf. Machine Learning, pp. 841-848, 2006.
-
(2006)
Proc. 23rd Int'l Conf. Machine Learning
, pp. 841-848
-
-
Sindhwani, V.1
Keerthi, S.S.2
Chapelle, O.3
-
38
-
-
84863338319
-
Unlabeled Data: Now It Helps, Now It Doesn't
-
A. Singh, R. Nowak, and X. Zhu, "Unlabeled Data: Now It Helps, Now It Doesn't," Proc. Advances in Neural Information Processing Systems, vol. 21, pp. 1513-1520, 2009.
-
(2009)
Proc. Advances in Neural Information Processing Systems
, vol.21
, pp. 1513-1520
-
-
Singh, A.1
Nowak, R.2
Zhu, X.3
-
39
-
-
33749018252
-
An Analysis of Diversity Measures
-
E.K. Tang, P.N. Suganthan, and X. Yao, "An Analysis of Diversity Measures," Machine Learning, vol. 65, no. 1, pp. 247-271, 2006.
-
(2006)
Machine Learning
, vol.65
, Issue.1
, pp. 247-271
-
-
Tang, E.K.1
Suganthan, P.N.2
Yao, X.3
-
41
-
-
56449085512
-
Graph Transduction via Alternating Minimization
-
J. Wang, T. Jebara, and S.-F. Chang, "Graph Transduction via Alternating Minimization," Proc. 25th Int'l Conf. Machine Learning, pp. 1144-1151, 2008.
-
(2008)
Proc. 25th Int'l Conf. Machine Learning
, pp. 1144-1151
-
-
Wang, J.1
Jebara, T.2
Chang, S.-F.3
-
42
-
-
17744409615
-
Bootstrapping SVM Active Learning by Incorporating Unlabelled Images for Image Retrieval
-
L. Wang, K. Chan, and Z. Zhang, "Bootstrapping SVM Active Learning by Incorporating Unlabelled Images for Image Retrieval," Proc. IEEE Conf. Computer Vision and Pattern Recognition, pp. 629-634, 2003.
-
(2003)
Proc. IEEE Conf. Computer Vision and Pattern Recognition
, pp. 629-634
-
-
Wang, L.1
Chan, K.2
Zhang, Z.3
-
44
-
-
0037686659
-
The Concave-Convex Procedure
-
A.L. Yuille and A. Rangarajan, "The Concave-Convex Procedure," Neural Computation, vol. 15, no. 4, pp. 915-936, 2003.
-
(2003)
Neural Computation
, vol.15
, Issue.4
, pp. 915-936
-
-
Yuille, A.L.1
Rangarajan, A.2
-
45
-
-
71149121119
-
Prototype Vector Machine for Large Scale Semi-Supervised Learning
-
K. Zhang, J.T. Kwok, and B. Parvin, "Prototype Vector Machine for Large Scale Semi-Supervised Learning," Proc. 26th Int'l Conf. Machine Learning, pp. 1233-1240, 2009.
-
(2009)
Proc. 26th Int'l Conf. Machine Learning
, pp. 1233-1240
-
-
Zhang, K.1
Kwok, J.T.2
Parvin, B.3
-
46
-
-
34547987546
-
Maximum Margin Clustering Made Practical
-
K. Zhang, I.W. Tsang, and J.T. Kwok, "Maximum Margin Clustering Made Practical," Proc. 24th Int'l Conf. Machine Learning, pp. 1119-1126, 2007.
-
(2007)
Proc. 24th Int'l Conf. Machine Learning
, pp. 1119-1126
-
-
Zhang, K.1
Tsang, I.W.2
Kwok, J.T.3
-
47
-
-
0005004572
-
The Value of Unlabeled Data for Classification Problems
-
T. Zhang and F. Oles, "The Value of Unlabeled Data for Classification Problems," Proc. 17th Int'l Conf. Machine Learning, pp. 1191-1198, 2000.
-
(2000)
Proc. 17th Int'l Conf. Machine Learning
, pp. 1191-1198
-
-
Zhang, T.1
Oles, F.2
-
48
-
-
84899006908
-
Learning with Local and Global Consistency
-
D. Zhou, O. Bousquet, T.Navin Lal, J. Weston, and B. Schölkopf, "Learning with Local and Global Consistency," Proc. Advances in Neural Information Processing Systems , vol. 16, pp. 595-602, 2004.
-
(2004)
Proc. Advances in Neural Information Processing Systems
, vol.16
, pp. 595-602
-
-
Zhou, D.1
Bousquet, O.2
Lal, T.N.3
Weston, J.4
Schölkopf, B.5
-
50
-
-
28244448186
-
Tri-Training: Exploiting Unlabeled Data Using Three Classifiers
-
Nov.
-
Z.-H. Zhou and M. Li, "Tri-Training: Exploiting Unlabeled Data Using Three Classifiers," IEEE Trans. Knowledge and Data Eng., vol. 17, no. 11, pp. 1529-1541, Nov. 2005.
-
(2005)
IEEE Trans. Knowledge and Data Eng.
, vol.17
, Issue.11
, pp. 1529-1541
-
-
Zhou, Z.-H.1
Li, M.2
-
51
-
-
77956708689
-
Semi-Supervised Learning by Disagreement
-
Z.-H. Zhou and M. Li, "Semi-Supervised Learning by Disagreement," Knowledge and Information Systems, vol. 24, no. 3, pp. 415-439, 2010.
-
(2010)
Knowledge and Information Systems
, vol.24
, Issue.3
, pp. 415-439
-
-
Zhou, Z.-H.1
Li, M.2
-
53
-
-
1942484430
-
Semi-Supervised Learning Using Gaussian Fields and Harmonic Functions
-
X. Zhu, Z. Ghahramani, and J. Lafferty, "Semi-Supervised Learning Using Gaussian Fields and Harmonic Functions," Proc. 20th Int'l Conf. Machine Learning, pp. 912-919, 2003.
-
(2003)
Proc. 20th Int'l Conf. Machine Learning
, pp. 912-919
-
-
Zhu, X.1
Ghahramani, Z.2
Lafferty, J.3
|