14.2.4 Semi-Supervised Clustering, Classification

Verbeek, J.J.[Jakob J.], Vlassis, N.[Nikos],
Gaussian fields for semi-supervised regression and correspondence learning,
PR(39), No. 10, October 2006, pp. 1864-1875.
WWW Version. Keywords: Gaussian fields; Regression; Active learning; Model selection 0606
BibRef

Ng, M.K.[Michael K.], Chan, E.Y.[Elaine Y.], So, M.M.C.[Meko M.C.], Ching, W.K.[Wai-Ki],
A semi-supervised regression model for mixed numerical and categorical variables,
PR(40), No. 6, June 2007, pp. 1745-1752.
WWW Version. 0704
Clustering; Regression; Data mining; Numerical variables; Categorical variables BibRef

Song, Y.Q.[Yang-Qiu], Nie, F.P.[Fei-Ping], Zhang, C.S.[Chang-Shui],
Semi-supervised sub-manifold discriminant analysis,
PRL(29), No. 13, 1 October 2008, pp. 1806-1813.
WWW Version. 0804
Semi-supervised learning; Dimensionality reduction; Sub-manifold discriminative embedding BibRef

Song, Y.Q.[Yang-Qiu], Nie, F.P.[Fei-Ping], Zhang, C.S.[Chang-Shui], Xiang, S.M.[Shi-Ming],
A unified framework for semi-supervised dimensionality reduction,
PR(41), No. 9, September 2008, pp. 2789-2799.
WWW Version. 0806
Dimensionality reduction; Discriminant analysis, Manifold analysis; Semi-supervised learning BibRef

Angelini, L.[Leonardo], Marinazzo, D.[Daniele], Pellicoro, M.[Mario], Stramaglia, S.[Sebastiano],
Semi-supervised learning by search of optimal target vector,
PRL(29), No. 1, 1 January 2008, pp. 34-39.
WWW Version. 0711
Semi-supervised learning; Kernel principal components; Transductive inference BibRef

Begleiter, R.[Ron], El-Yaniv, R.[Ran], Pechyony, D.[Dmitry],
Repairing self-confident active-transductive learners using systematic exploration,
PRL(29), No. 9, 1 July 2008, pp. 1245-1251.
WWW Version. 0711
Active learning; Transductive learning; Semi-supervised clustering BibRef

Come, E., Oukhellou, L., Denoeux, T., Aknin, P.,
Learning from partially supervised data using mixture models and belief functions,
PR(42), No. 3, March 2009, pp. 334-348.
WWW Version. 0811
Dempster-Shafer theory; Transferable belief model; Mixture models; EM algorithm; Classification; Clustering; Partially supervised learning; Semi-supervised learning BibRef

Wang, J.D.[Jing-Dong], Wang, F.[Fei], Zhang, C.S.[Chang-Shui], Shen, H.C.[Helen C.], Quan, L.[Long],
Linear Neighborhood Propagation and Its Applications,
PAMI(31), No. 9, September 2009, pp. 1600-1615.
IEEE DOI Link 0907
BibRef

Wang, F.[Fei], Zhang, C.S.[Chang-Shui], Shen, H.C.[Helen C.], Wang, J.D.[Jing-Dong],
Semi-Supervised Classification Using Linear Neighborhood Propagation,
CVPR06(I: 160-167).
IEEE DOI Link 0606
BibRef

Mallapragada, P.K.[Pavan Kumar], Jin, R.[Rong], Jain, A.K.[Anil K.], Liu, Y.[Yi],
SemiBoost: Boosting for Semi-Supervised Learning,
PAMI(31), No. 11, November 2009, pp. 2000-2014.
IEEE DOI Link 0910
BibRef
Earlier: A1, A2, A3, Only:
Active query selection for semi-supervised clustering,
ICPR08(1-4).
IEEE DOI Link 0812
BibRef

Fu, Y.[Yun], Li, Z.[Zhu], Zhou, X.[Xi], Huang, T.S.[Thomas S.],
Laplacian Affinity Propagation for Semi-Supervised Object Classification,
ICIP07(I: 189-192).
IEEE DOI Link 0709
graph-based learning algorithm BibRef

Yang, W.[Wuyi], Zhang, S.[Shuwu], Liang, W.[Wei],
A Graph Based Subspace Semi-supervised Learning Framework for Dimensionality Reduction,
ECCV08(II: 664-677).
Springer DOI Link 0810
BibRef

Zhang, Z.Y.[Zhen-Yue], Zha, H.Y.[Hong-Yuan], Zhang, M.[Min],
Spectral methods for semi-supervised manifold learning,
CVPR08(1-6).
IEEE DOI Link 0806
BibRef

Gong, Y.C.[Yun-Chao], Chen, C.L.[Chuan-Liang], Tian, Y.J.[Yin-Jie],
Graph-based semi-supervised learning with redundant views,
ICPR08(1-4).
IEEE DOI Link 0812
BibRef

Korecki, J.N.[John N.], Banfield, R.E.[Robert E.], Hall, L.O.[Lawrence O.], Bowyer, K.W.[Kevin W.], Kegelmeyer, W.P.[W. Philip],
Semi-supervised learning on large complex simulations,
ICPR08(1-4).
IEEE DOI Link 0812
BibRef

Hu, J.Y.[Jian-Ying], Singh, M.[Moninder], Mojsilovic, A.[Aleksandra],
Categorization using semi-supervised clustering,
ICPR08(1-4).
IEEE DOI Link 0812
BibRef

Cheng, Y.[Yubo], Cai, Y.P.[Yun-Peng], Sun, Y.J.[Yi-Jun], Li, J.[Jian],
Semi-supervised feature selection under logistic I-RELIEF framework,
ICPR08(1-4).
IEEE DOI Link 0812
BibRef

Xiao, R.[Rui], Shi, P.F.[Peng-Fei],
Semi-supervised marginal discriminant analysis based on QR decomposition,
ICPR08(1-4).
IEEE DOI Link 0812
BibRef

Qiu, H.N.[Hui-Ning], Lai, J.H.[Jian-Huang], Huang, J.[Jian], Chen, Y.[Yu],
Semi-supervised discriminant analysis based on UDP regularization,
ICPR08(1-4).
IEEE DOI Link 0812
BibRef

Tahir, M.A.[Muhammad Atif], Smith, J.E.[James E.], Caleb-Solly, P.[Praminda],
A Novel Feature Selection Based Semi-supervised Method for Image Classification,
CVS08(xx-yy).
Springer DOI Link 0805
See also Simultaneous feature selection and feature weighting using Hybrid Tabu Search/K-nearest neighbor classifier. BibRef

Liu, R.J.[Ru-Jie], Wang, Y.[Yuehong], Baba, T.[Takayuki], Masumoto, D.[Daiki],
Semi-supervised learning by locally linear embedding in kernel space,
ICPR08(1-4).
IEEE DOI Link 0812
BibRef

Adankon, M.M.[Mathias M.], Cheriet, M.[Mohamed],
Help-training for semi-supervised discriminative classifiers. Application to SVM,
ICPR08(1-4).
IEEE DOI Link 0812
BibRef

Batra, D., Sukthankar, R., Chen, T.,
Semi-Supervised Clustering via Learnt Codeword Distances,
BMVC08(xx-yy).
PDF Version. 0809
BibRef

Marin-Castro, H.[Heidy], Sucar, E.[Enrique], Morales, E.[Eduardo],
Automatic Image Annotation Using a Semi-supervised Ensemble of Classifiers,
CIARP07(487-495).
Springer DOI Link 0711
BibRef

Didaci, L.[Luca], Roli, F.[Fabio],
Using Co-training and Self-training in Semi-supervised Multiple Classifier Systems,
SSPR06(522-530).
Springer DOI Link 0608
BibRef

Zhang, R.[Rong], Rudnicky, A.I.[Alexander I.],
A New Data Selection Principle for Semi-Supervised Incremental Learning,
ICPR06(II: 780-783).
WWW Version. 0609
BibRef

Gong, H.F.[Hai-Feng], Pan, C.H.[Chun-Hong], Yang, Q.[Qing], Lu, H.Q.[Han-Qing], Ma, S.D.[Song-De],
Neural Network Modeling of Spectral Embedding,
BMVC06(I:227).
PDF Version. 0609
BibRef
Earlier:
A Semi-Supervised Framework for Mapping Data to the Intrinsic Manifold,
ICCV05(I: 98-105).
IEEE DOI Link 0510
Reduce dimensionality, but to the intrinsic form. BibRef

Duan, R.[Rong], Jiang, W.[Wei], Man, H.[Hong],
Semi-Supervised Image Classification in Likelihood Space,
ICIP06(957-960). 0610

IEEE DOI Link BibRef
And:
Robust Adjusted Likelihood Function for Image Analysis,
AIPR06(29-29).
IEEE DOI Link 0610
BibRef

Song, Y.Q.[Yang-Qiu], Zhang, C.S.[Chang-Shui], Lee, J.G.[Jian-Guo],
Graph Based Multi-class Semi-supervised Learning Using Gaussian Process,
SSPR06(450-458).
Springer DOI Link 0608
BibRef

Rosenberg, C.[Chuck], Hebert, M.[Martial], Schneiderman, H.[Henry],
Semi-Supervised Self-Training of Object Detection Models,
WACV05(I: 29-36).
WWW Version. 0502
BibRef

Rosenberg, C., Hebert, M.,
Training Object Detection Models with Weakly Labeled Data,
BMVC02(Poster Session). 0208
BibRef

Saint-Jean, C., Frelicot, C.,
A robust semi-supervised EM-based clustering algorithm with a reject option,
ICPR02(III: 399-402).
IEEE DOI Link 0211
BibRef

Chapter on Pattern Recognition, Clustering, Statistics, Grammars, Learning, Neural Nets, Genetic Algorithms continues in
Iterative, Hierarchical Clustering Techniques .