Semi-Supervised Learning

Semi-Supervised Learning via Generalized Maximum Entropy AISTATS 2010 Semi-Supervised Learning with Adversarially Missing Label Information NeurIPS 2010 Semi-Supervised Learning with Max-Margin Graph Cuts AISTATS 2010 Semi-Supervised Novelty Detection JMLR 2010 Sparse Semi-supervised Learning Using Conjugate Functions JMLR 2010 Transduction with Matrix Completion: Three Birds with One Stone NeurIPS 2010 3D Object Recognition with Deep Belief Nets NeurIPS 2009 Adaptive Regularization for Transductive Support Vector Machine NeurIPS 2009 A Rate Distortion Approach for Semi-Supervised Conditional Random Fields NeurIPS 2009 Augmenting Feature-driven fMRI Analyses: Semi-supervised learning and resting state activity NeurIPS 2009 Distribution Matching for Transduction NeurIPS 2009 Dual Averaging Method for Regularized Stochastic Learning and Online Optimization NeurIPS 2009 Entropic Graph Regularization in Non-Parametric Semi-Supervised Classification NeurIPS 2009 Label Selection on Graphs NeurIPS 2009 Learning Bregman Distance Functions and Its Application for Semi-Supervised Clustering NeurIPS 2009 Learning from Multiple Partially Observed Views - an Application to Multilingual Text Categorization NeurIPS 2009 Manifold Regularization for SIR with Rate Root-n Convergence NeurIPS 2009 Multi-Label Prediction via Sparse Infinite CCA NeurIPS 2009 Nonlinear Learning using Local Coordinate Coding NeurIPS 2009 On Efficient Large Margin Semisupervised Learning: Method and Theory JMLR 2009 Semi-Supervised Learning in Gigantic Image Collections NeurIPS 2009 Semi-supervised Learning using Sparse Eigenfunction Bases NeurIPS 2009 Semi-supervised Regression using Hessian energy with an application to semi-supervised dimensionality reduction NeurIPS 2009 Semi-Supervised Training for the Averaged Perceptron POS Tagger EACL 2009 Statistical Analysis of Semi-Supervised Learning: The Limit of Infinite Unlabelled Data NeurIPS 2009