Active Bibliography

2 ON SEMI-SUPERVISED KERNEL METHODS – Vikas Sindhwani
2 New Theoretical Frameworks for Machine Learning – Maria-florina Balcan, Manuel Blum, Yishay Mansour, Tom Mitchell, Santosh Vempala - 2007
Learning with Unlabeled Data – Xu Zenglin
UNSUPERVISED FEATURE LEARNING VIA SPARSE HIERARCHICAL REPRESENTATIONS – Honglak Lee
3 Regularized Adaptation: Theory, Algorithms and Applications – Xiao Li - 2007
41 Using Unlabeled Data to Improve Text Classification – Kamal Paul Nigam - 2001
197 Manifold regularization: A geometric framework for learning from examples – Mikhail Belkin, Partha Niyogi, Vikas Sindhwani, Peter Bartlett - 2004
Techniques for Exploiting Unlabeled Data – Mugizi Robert Rwebangira, Avrim Blum, John Lafferty - 2008
6 A Discriminative Model for Semi-Supervised Learning – Maria-Florina Balcan, Avrim Blum - 2008
157 Analyzing the Effectiveness and Applicability of Co-training – Kamal Nigam, Rayid Ghani - 2000
19 Semi-supervised regression with co-training style algorithms – Zhi-hua Zhou, Ming Li - 2007
33 Active Learning with Multiple Views – Ion Alexandru Muslea - 2002
Learning by Combining Native Features with Similarity Functions – Mugizi Robert Rwebangira, Avrim Blum - 2009
Local Linear Semi-supervised Regression – Mugizi Robert Rwebangira, John Lafferty - 2009
24 Understanding the Behavior of Co-training – Kamal Nigam, Rayid Ghani - 2000
1 Scaling up semi-supervised learning: an efficient and effective llgc variant – Bernhard Pfahringer, Claire Leschi, Peter Reutemann - 2006
Predictive Modeling using . . . – Amrudin Agovic - 2011
Bayesian Learning for Efficient Visual Inference – Oliver Michael Christian Williams - 2005
Probabilistic Graphical Models and Algorithms for Protein Problems – Feng Jiao - 2007