semi-supervised learning

Generalization Error Bounds in Semi-supervised Classification Under the Cluster Assumption JMLR 2007 Graph Laplacians and their Convergence on Random Neighborhood Graphs JMLR 2007 Large Margin Semi-supervised Learning JMLR 2007 On the Effectiveness of Laplacian Normalization for Graph Semi-supervised Learning JMLR 2007 Regularized Boost for Semi-Supervised Learning NeurIPS 2007 Scene Segmentation with CRFs Learned from Partially Labeled Images NeurIPS 2007 Semi-Supervised Multitask Learning NeurIPS 2007 Statistical Analysis of Semi-Supervised Regression NeurIPS 2007 The Value of Labeled and Unlabeled Examples when the Model is Imperfect NeurIPS 2007 Branch and Bound for Semi-Supervised Support Vector Machines NeurIPS 2006 Clustering Under Prior Knowledge with Application to Image Segmentation NeurIPS 2006 Enhancing Supervised Terrain Classification with Predictive Unsupervised Learning RSS 2006 Fast SDP Relaxations of Graph Cut Clustering, Transduction, and Other Combinatorial Problems JMLR 2006 Hyperparameter Learning for Graph Based Semi-supervised Learning Algorithms NeurIPS 2006 Large-Scale Sparsified Manifold Regularization NeurIPS 2006 Large Scale Transductive SVMs JMLR 2006 Learning on Graph with Laplacian Regularization NeurIPS 2006 Learning to Model Spatial Dependency: Semi-Supervised Discriminative Random Fields NeurIPS 2006 Manifold Denoising NeurIPS 2006 Manifold Regularization: A Geometric Framework for Learning from Labeled and Unlabeled Examples JMLR 2006 On the Relation Between Low Density Separation, Spectral Clustering and Graph Cuts NeurIPS 2006 Part-based Probabilistic Point Matching using Equivalence Constraints NeurIPS 2006 Relational Learning with Gaussian Processes NeurIPS 2006 Worst-Case Analysis of Selective Sampling for Linear Classification JMLR 2006 A Framework for Learning Predictive Structures from Multiple Tasks and Unlabeled Data JMLR 2005