Semi-Supervised Learning Literature Survey

Semi-Supervised Learning Literature Survey (2006)

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by Xiaojin Zhu

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@MISC{Zhu06semi-supervisedlearning,
    author = {Xiaojin Zhu},
    title = {Semi-Supervised Learning Literature Survey},
    year = {2006}
}

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Abstract

We review the literature on semi-supervised learning, which is an area in machine learning and more generally, artificial intelligence. There has been a whole spectrum of interesting ideas on how to learn from both labeled and unlabeled data, i.e. semi-supervised learning. This document is a chapter excerpt from the author’s doctoral thesis (Zhu, 2005). However the author plans to update the online version frequently to incorporate the latest development in the field. Please obtain the latest version at http://www.cs.wisc.edu/~jerryzhu/pub/ssl_survey.pdf

Citations

8141	Statistical Learning Theory - Vapnik - 1998
7486	Maximum likelihood from incomplete data via the EM algorithm (with discussion - Dempster, Laird, et al. - 1977
3964	A tutorial on hidden Markov models and selected applications in speech recognition - Rabiner - 1989
2325	Normalized Cuts and Image Segmentation - Shi, Malik
2063	Latent Dirichlet allocation - Blei, Ng, et al.
1540	A global geometric framework for nonlinear dimensionality reduction, Science - Tenenbaum, Silva, et al. - 2000
1451	Nonlinear dimensionality reduction by locally linear embedding, Science - Roweis, Saul - 2000
1158	Combining labeled and unlabeled data with co-training - Blum, Mitchell - 1998
968	On Spectral Clustering: Analysis and an Algorithm - Ng, Jordan, et al. - 2001
762	Text classification from labeled and unlabeled documents using - Nigam, McCallum, et al.
707	A Comparison of Event Models for naïve Bayes Text Classification - McCallum, Nigam - 1998
659	P.: Laplacian eigenmaps for dimensionality reduction and data representation - Belkin, Niyogi - 2003
626	Transductive inference for text classification using support vector machines - Joachims - 1999
499	Probabilistic latent semantic analysis - Hofmann - 1999
460	Unsupervised word sense disambiguation rivaling supervised methods - Yarowsky - 1995
438	Semi-Supervised Learning Using Gaussian Fields and Harmonic Functions - Zhu, Ghahramani, et al. - 2003
416	Unsupervised models for named entity classification - Collins, Singer - 1999
414	Machine learning - Mitchell - 1997
382	Learning with local and global consistency - ZHOU, BOUSQUET, et al. - 2004
374	Exploiting generative models in discriminative classifiers - Jaakkola, Haussler - 1999
331	A sentimental education: Sentiment analysis using subjectivity summarization based on minimum cuts - Pang, Lee - 2004
300	Segmentation using eigenvectors: a unifying view - Weiss - 1999
278	Manifold regularization: A geometric framework for learning from labeled and unlabeled examples - Belkin, Niyogi, et al. - 2006
278	A framework for learning predictive structures from multiple tasks and unlabeled data - Ando, Zhang - 2005
248	A Tutorial on Spectral Clustering - Luxburg - 2007
245	Learning from labeled and unlabeled data using graph mincuts - Blum, Chawla - 2001
237	Employing EM and poolbased active learning for text classification - McCallum, Nigam - 1998
235	S.T.: Think globally, fit locally: Unsupervised learning of low dimensional manifolds - Saul, Roweis - 2003
228	Semi-Supervised Learning - Chapelle, Schölkopf, et al. - 2006
188	Partially labeled classification with Markov random walks - Szummer, Jaakkola - 2001
181	Analyzing the effectiveness and applicability of cotraining - NIGAM, GHANI - 2000
177	Transductive learning via spectral graph partitioning - Joachims - 2003
168	Semi-supervised support vector machines - BENNETT, DEMIRIZ - 1999
164	Hessian Eigenmaps: Locally Linear Embedding Techniques for High-dimensional Data - Donoho, Grimes
163	Diffusion kernels on graphs and other discrete input spaces - Kondor, Lafferty - 2002
162	Self-taught learning: Transfer learning from unlabeled data - Raina, Battle, et al.
155	Spectral grouping using the nystrom method - Fowlkes, Belongie, et al.
150	Kernels and regularization on graphs - Smola, Kondor - 2003
150	Unsupervised Learning of Image Manifolds by Semidefinite Programming - Weinberger, Saul
140	Cluster kernels for semi-supervised learning - Chapelle, Weston, et al. - 2003
137	Colorization using optimization - LEVIN, LISCHINSKI, et al. - 2004
118	Enhancing supervised learning with unlabeled data - Goldman, Zhou - 2000
112	Integrating topics and syntax - Griffiths, Steyvers, et al. - 2005
112	Maximum entropy discrimination - Jaakkola, Meila, et al. - 1999
109	Semi-supervised classification by low density separation - Chapelle, Zien - 2005
109	Learning subjective nouns using extraction pattern bootstrapping - Riloff, Wiebe, et al. - 2003
100	Learning a kernel matrix for nonlinear dimensionality reduction - Weinberger, Sha, et al.
99	A Mixture of Experts Classifier with Learning Based on Both Labelled and Unlabelled Data - Miller, Uyar - 1996
97	Beyond the point cloud: from transductive to semi-supervised learning - Sindhwani, Niyogi, et al.
96	Regularization and semi-supervised learning on large graphs - Belkin, Matveeva, et al. - 2004