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In recent years, a great many methods of learning from multi-view data by considering the diversity of different views have been proposed.
Relations between two sets of variates
H. Hotelling · 1936
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Spline models for observational data (philadelphia, pa: Siam)
G. Wahba · 1990
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Query by committee
H.S. Seung, M. Opper, and H. Sompolinsky · 1992
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Bagging predictors
L. Breiman · 1996
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Experiments with a new boosting algorithm
Y. Freund and R.E. Schapire · 1996
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Feature selection: Evaluation, application, and small sample performance
A. Jain and D. Zongker · 1997
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Combining labeled and unlabeled data with co-training
A. Blum and T. Mitchell · 1998
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The random subspace method for constructing decision forests
T.K. Ho · 1998
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Learning to construct knowledge bases from the world wide web
M. Craven, D. DiPasquo, D. Freitag, A. McCallum, T. Mitchell, K. Nigam, and S. Slattery · 2000
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Leveraging for regression
N. Duffy and D. Helmbold · 2000
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Enhancing supervised learning with unlabeled data
S. Goldman and Y. Zhou · 2000
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Ensemble learning
H. Lappalainen and J. Miskin · 2000
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Selective sampling with co-testing
I. Muslea, S. Minton, and C.A. Knoblock · 2000
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Analyzing the effectiveness and applicability of co-training
K. Nigam and R. Ghani · 2000
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The elements of statistical learning , volume 1
J. Friedman, T. Hastie, and R. Tibshirani · 2001
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Email classification with co-training
S. Kiritchenko and S. Matwin · 2001
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Limitations of co-training for natural language learning from large datasets
D. Pierce and C. Cardie · 2001
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Composite kernels for hypertext categorisation
Nello Cristianini Thorsten Joachims and John Shawe-Taylor · 2001
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Bootstrapping
Steven Abney · 2002
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Mark: A boosting algorithm for heterogeneous kernel models
K.P. Bennett, M. Momma, and M.J. Embrechts · 2002
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Kernel design using boosting
K. Crammer, J. Keshet, and Y. Singer · 2002
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Pac generalization bounds for co-training
S. Dasgupta, M.L. Littman, and D. McAllester · 2002
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Ensemble learning
T.G. Dietterichl · 2002
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Learning the kernel matrix with semi-definite programming
G.R.G. Lanckriet, N. Cristianini, L. El Ghaoui, P. Bartlett, and M.I. Jordan · 2002
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Applying co-training to reference resolution
C. Müller, S. Rapp, and M. Strube · 2002
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Exploiting strong syntactic heuristics and co-training to learn semantic lexicons
W. Phillips and E. Riloff · 2002
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A bootstrapping approach to annotating large image collection
H.M. Feng and T.S. Chua · 2003
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An introduction to variable and feature selection
I. Guyon and A. Elisseeff · 2003
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Using transduction and multi-view learning to answer emails
M. Kockelkorn, A. Lüneburg, and T. Scheffer · 2003
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Active learning with strong and weak views: A case study on wrapper induction
I. Muslea, S.N. Minton, and C.A. Knoblock · 2003
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Multiple kernel learning, conic duality, and the smo algorithm
F.R. Bach, G.R.G. Lanckriet, and M.I. Jordan · 2004
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Co-training and expansion: Towards bridging theory and practice
M.F. Balcan, A. Blum, and Y. Ke · 2004
Earlier work this paper cites.
Column-generation boosting methods for mixture of kernels
J. Bi, T. Zhang, and K.P. Bennett · 2004
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Multi-view clustering
S. Bickel and T. Scheffer · 2004
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Co-em support vector learning
U. Brefeld and T. Scheffer · 2004
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A bootstrapping framework for annotating and retrieving www images
H. Feng, R. Shi, and T.S. Chua · 2004
Earlier work this paper cites.
Learning the kernel matrix with semidefinite programming
G.R.G. Lanckriet, N. Cristianini, P. Bartlett, L.E. Ghaoui, and M.I. Jordan · 2004
Earlier work this paper cites.
Gaussian process latent variable models for visualisation of high dimensional data
N.D. Lawrence · 2004
Earlier work this paper cites.
Co-training for predicting emotions with spoken dialogue data
B. Maeireizo, D. Litman, and R. Hwa · 2004
Earlier work this paper cites.
Co-training and self-training for word sense disambiguation
R. Mihalcea · 2004
Earlier work this paper cites.
Email answering assistance by semi-supervised text classification
T. Scheffer · 2004
Earlier work this paper cites.
Exploiting unlabeled data in content-based image retrieval
Z.H. Zhou, K.J. Chen, and Y. Jiang · 2004
Earlier work this paper cites.
Multi-view discriminative sequential learning
U. Brefeld, C. Büscher, and T. Scheffer · 2005
Earlier work this paper cites.
Two view learning: Svm-2k, theory and practice
J. Farquhar, D. Hardoon, H. Meng, J. Shawe-Taylor, and S. Szedmak · 2005
Cited alongside, same era.
Multi-view semi-supervised learning: An approach to obtain different views from text datasets
E.T. Matsubara, M.C. Monard, and G.E. Batista · 2005
Cited alongside, same era.
A co-regularization approach to semi-supervised learning with multiple views
V. Sindhwani, P. Niyogi, and M. Belkin · 2005
Cited alongside, same era.
Semi-supervised cross feature learning for semantic concept detection in videos
R. Yan and M. Naphade · 2005
Cited alongside, same era.
A kernel method for canonical correlation analysis
S. Akaho · 2006
Cited alongside, same era.
Efficient co-regularised least squares regression
U. Brefeld, T. Gärtner, T. Scheffer, and S. Wrobel · 2006
Cited alongside, same era.
Active learning literature survey
Burr Settles · 2009
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Shared kernel information embedding for discriminative inference
L. Sigal, R. Memisevic, and D.J. Fleet · 2009
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More generality in efficient multiple kernel learning
M. Varma and B.R. Babu · 2009
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Co-training for cross-lingual sentiment classification
X. Wan · 2009
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Generalization bounds for learning the kernel
Y. Ying and C. Campbell · 2009
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Patch alignment for dimensionality reduction
T. Zhang, D. Tao, X. Li, and J. Yang · 2009
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Fast active appearance model search using canonical correlation analysis
R. Donner, M. Reiter, G. Langs, P. Peloschek, and H. Bischof · 2006
Cited alongside, same era.
Support vector machine learning from heterogeneous data: an empirical analysis using protein sequence and structure
D.P. Lewis, T. Jebara, and W.S. Noble · 2006
Cited alongside, same era.
Multitraining support vector machine for image retrieval
J. Li, N. Allinson, D. Tao, and X. Li · 2006
Cited alongside, same era.
Kernel information embeddings
R. Memisevic · 2006
Cited alongside, same era.
Active learning with multiple views
I. Muslea, S. Minton, and C.A. Knoblock · 2006
Cited alongside, same era.
Learning shared latent structure for image synthesis and robotic imitation
A. Shon, K. Grochow, A. Hertzmann, and R. Rao · 2006
Cited alongside, same era.
M.R. Amini and C. Goutte · 2010
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Learning from multiple partially observed views-an application to multilingual text categorization
M.R. Amini, N. Usunier, C. Goutte, et al · 2010
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Multiview clustering with incomplete views
Hal Daum¨¦ III Scott L. DuVall Anusua Trivedi, Piyush Rai · 2010
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Predictive subspace learning for multi-view data: A large margin approach
N. Chen, J. Zhu, and E.P. Xing · 2010
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Generalization bounds for learning kernels
C. Cortes, M. Mohri, and A. Rostamizadeh · 2010
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Factorized latent spaces with structured sparsity
Y. Jia, M. Salzmann, and T. Darrell · 2010
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Co-regularized spectral clustering with multiple kernels
A. Kumar, P. Rai, and H. Daumé III · 2010
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Factorized orthogonal latent spaces
M. Salzmann, C.H. Ek, R. Urtasun, and T. Darrell · 2010
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Sparse multiple kernel learning for signal processing applications
N. Subrahmanya and Y.C. Shin · 2010
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Composite kernel learning
M. Szafranski, Y. Grandvalet, and A. Rakotomamonjy · 2010
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A new analysis of co-training
W. Wang and Z.H. Zhou · 2010
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Cross lingual adaptation: An experiment on sentiment classifications
B. Wei and C. Pal · 2010
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Multiview spectral embedding
T. Xia, D. Tao, T. Mei, and Y. Zhang · 2010
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Simple and efficient multiple kernel learning by group lasso
Z. Xu, R. Jin, H. Yang, I. King, and M.R. Lyu · 2010
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Convergence rate of kernel canonical correlation analysis
J. Cai and H.W. Sun · 2011
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Automatic feature decomposition for single view co-training
M. Chen, K.Q. Weinberger, and Y. Chen · 2011
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Multi-view learning of word embeddings via cca
P.S. Dhillon, D. Foster, and L. Ungar · 2011
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Multiple kernel learning algorithms
M. Gönen and E. Alpaydın · 2011
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The local rademacher complexity of lp-norm multiple kernel learning
M. Kloft and G. Blanchard · 2011
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A co-training approach for multi-view spectral clustering
A. Kumar and H. Daumé III · 2011
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Co-regularized multi-view spectral clustering
A. Kumar, P. Rai, and H. Daumé III · 2011
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Difficulty guided image retrieval using linear multiview embedding
Y. Li, B. Geng, Z.J. Zha, D. Tao, L. Yang, and C. Xu · 2011
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A boosted co-training algorithm for human action recognition
C. Liu and P.C. Yuen · 2011
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Learning multi-view neighborhood preserving projections
N. Quadrianto and C.H. Lampert · 2011
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View construction for multi-view semi-supervised learning
S. Sun, F. Jin, and W. Tu · 2011
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Bi-weighting domain adaptation for cross-language text classification
C. Wan, R. Pan, and J. Li · 2011
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A novel multi-view learning developed from single-view patterns
Z. Wang, S. Chen, and D. Gao · 2011
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m-sne: Multiview stochastic neighbor embedding
B. Xie, Y. Mu, D. Tao, and K. Huang · 2011
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Bayesian co-training
S. Yu, B. Krishnapuram, R. Rosales, and R.B. Rao · 2011
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View generation for multiview maximum disagreement based active learning for hyperspectral image classification
W. Di and M.M. Crawford · 2012
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Sparse unsupervised dimensionality reduction for multiple view data
Y. Han, F. Wu, D. Tao, J. Shao, Y. Zhuang, and J. Jiang · 2012
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Shared kernel information embedding for discriminative inference
R. Memisevic, L. Sigal, and D.J. Fleet · 2012
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Generalized multiview analysis: A discriminative latent space
A. Sharma, A. Kumar, H. Daume III, and D.W. Jacobs · 2012
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Multiview metric learning with global consistency and local smoothness
D. Zhai, H. Chang, S. Shan, X. Chen, and W. Gao · 2012
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On combining multiple features for hyperspectral remote sensing image classification
L. Zhang, D. Tao, and X. Huang · 2012
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Dimensionality reduction by mixed kernel canonical correlation analysis
X. Zhu, Z. Huang, H. Tao Shen, J. Cheng, and C. Xu · 2012
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