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

Mallapragada, P.K.[Pavan K.], Jin, R.[Rong], Jain, A.K.[Anil K.],
Online visual vocabulary pruning using pairwise constraints,
CVPR10(3073-3080).
IEEE DOI Link 1006
BibRef

Yin, X.S.[Xue-Song], Chen, S.C.[Song-Can], Hu, E.L.[En-Liang], Zhang, D.Q.[Dao-Qiang],
Semi-supervised clustering with metric learning: An adaptive kernel method,
PR(43), No. 4, April 2010, pp. 1320-1333.
Elsevier DOI Link
WWW Version. 1002
Metric learning; Pairwise constraint; Closure centroid; Semi-supervised clustering BibRef

Liu, B., Wang, M., Hong, R., Zha, Z., Hua, X.S.,
Joint Learning of Labels and Distance Metric,
SMC-B(40), No. 3, June 2010, pp. 973-978.
IEEE DOI Link 1006
Deal with lack of training data and poor distance metrics. Semi-supervised learning. BibRef

Shiga, M.[Motoki], Takigawa, I.[Ichigaku], Mamitsuka, H.[Hiroshi],
A spectral approach to clustering numerical vectors as nodes in a network,
PR(44), No. 2, February 2011, pp. 236-251.
Elsevier DOI Link
WWW Version. 1011
Semi-supervised clustering; Heterogeneous data; Data integration; Spectral clustering BibRef

Shiga, M.[Motoki], Mamitsuka, H.[Hiroshi],
Efficient semi-supervised learning on locally informative multiple graphs,
PR(45), No. 3, March 2012, pp. 1035-1049.
Elsevier DOI Link
WWW Version. 1111
Semi-supervised learning; Graph integration; Label propagation; Soft spectral clustering; EM (Expectation Maximization) algorithm BibRef

Chen, K.[Ke], Wang, S.H.[Shi-Hai],
Semi-Supervised Learning via Regularized Boosting Working on Multiple Semi-Supervised Assumptions,
PAMI(33), No. 1, January 2011, pp. 129-143.
IEEE DOI Link 1011
BibRef

Demir, B., Persello, C., Bruzzone, L.,
Batch-Mode Active-Learning Methods for the Interactive Classification of Remote Sensing Images,
GeoRS(49), No. 3, March 2011, pp. 1014-1031.
IEEE DOI Link 1103
BibRef

Chen, X.M.[Xiao-Ming], Liu, W.Q.[Wan-Quan], Qiu, H.N.[Hui-Ning], Lai, J.H.[Jian-Huang],
APSCAN: A parameter free algorithm for clustering,
PRL(32), No. 7, 1 May 2011, pp. 973-986.
Elsevier DOI Link
WWW Version. 1101
Clustering algorithm; DBSCAN; Affinity propagation algorithm 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

Adankon, M.M.[Mathias M.], Cheriet, M.[Mohamed],
Help-Training for semi-supervised support vector machines,
PR(44), No. 9, September 2011, pp. 2220-2230.
Elsevier DOI Link
WWW Version. 1106
BibRef
Earlier:
Help-training for semi-supervised discriminative classifiers. Application to SVM,
ICPR08(1-4).
IEEE DOI Link 0812
Classification; Semi-supervised learning; SVM; Kernel machine See also Optimizing resources in model selection for support vector machine. BibRef

Monaco, J.P., Madabhushi, A.,
Weighted Maximum Posterior Marginals for Random Fields Using an Ensemble of Conditional Densities From Multiple Markov Chain Monte Carlo Simulations,
MedImg(30), No. 7, July 2011, pp. 1353-1364.
IEEE DOI Link 1107
Adjust when some errors are more important than others. BibRef

Yang, T.[Ting], Priebe, C.E.[Carey E.],
The Effect of Model Misspecification on Semi-Supervised Classification,
PAMI(33), No. 10, October 2011, pp. 2093-2103.
IEEE DOI Link 1109
Training both on labeled and unlabeled observations. Using unlabeled points degrades result if the model is wrong. BibRef

Duvenaud, D.[David], Marlin, B.[Benjamin], Murphy, K.[Kevin],
Multiscale Conditional Random Fields for Semi-supervised Labeling and Classification,
CRV11(371-378).
IEEE DOI Link 1105
BibRef

Kimura, A.[Akisato], Kameoka, H.[Hirokazu], Sugiyama, M.[Masashi], Nakano, T.[Takuho], Maeda, E.[Eisaku], Sakano, H.[Hitoshi], Ishiguro, K.[Katsuhiko],
SemiCCA: Efficient Semi-supervised Learning of Canonical Correlations,
ICPR10(2933-2936).
IEEE DOI Link 1008
BibRef

Han, X.H.[Xian-Hua], Chen, Y.W.[Yen-Wei], Ruan, X.[Xiang],
Semi-supervised and Interactive Semantic Concept Learning for Scene Recognition,
ICPR10(3045-3048).
IEEE DOI Link 1008
BibRef

Chandel, A.S.[Arvind Singh], Tiwari, A.[Aruna], Chaudhari, N.S.[Narendra S.],
Constructive Semi-Supervised Classification Algorithm and Its Implement in Data Mining,
PReMI09(62-67).
Springer DOI Link 0912
BibRef

Du, W.W.[Wei-Wei], Urahama, K.[Kiichi],
Error-correcting semi-supervised learning with mode-filter on graphs,
Emergent09(2095-2100).
IEEE DOI Link 0910
Apply mode filter to deal with errors in training data. BibRef

Gui, J.[Jie], Huang, D.S.[De-Shuang], You, Z.H.[Zhu-Hong],
An improvement on learning with local and global consistency,
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.B.[Yu-Bo], 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

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.H.[Yue-Hong], Baba, T.[Takayuki], Masumoto, D.[Daiki],
Semi-supervised learning by locally linear embedding in kernel space,
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, L.E.[L. 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 .