← Learning Paradigms
Machine Learning › Learning Paradigms ›

Semi-Supervised Learning

714 directly classified papers

Papers per year

Papers

Transfer Learning in a Transductive Setting NIPS 2013
Manifold-based Similarity Adaptation for Label Propagation NIPS 2013
Correlated random features for fast semi-supervised learning NIPS 2013
Multi-task Vector Field Learning NIPS 2012
New Bounds for Learning Intervals with Implications for Semi-Supervised Learning COLT 2012
Learning with Target Prior NIPS 2012
Frustratingly Simplified Deployment in WLAN Localization by Learning from Route Annotation ACML 2012
More Is Better: Large Scale Partially-supervised Sentiment Classification ACML 2012
Forging The Graphs: A Low Rank and Positive Semidefinite Graph Learning Approach NIPS 2012
Deterministic Annealing for Semi-Supervised Structured Output Learning AISTATS 2012
A Variance Minimization Criterion to Active Learning on Graphs AISTATS 2012
Data dependent kernels in nearly-linear time AISTATS 2012
Semi-supervised Eigenvectors for Locally-biased Learning NIPS 2012
Unsupervised Supervised Learning II: Margin-Based Classification without Labels AISTATS 2011
Semi-supervised Learning by Higher Order Regularization AISTATS 2011
Error Analysis of Laplacian Eigenmaps for Semi-supervised Learning AISTATS 2011
Semi-Supervised Learning with Measure Propagation JMLR 2011
The Impact of Unlabeled Patterns in Rademacher Complexity Theory for Kernel Classifiers NIPS 2011
Semi-Supervised Learning with Max-Margin Graph Cuts AISTATS 2010
Relating Function Class Complexity and Cluster Structure in the Function Domain with Applications to Transduction AISTATS 2010
Learning from Candidate Labeling Sets NIPS 2010
Inductive Regularized Learning of Kernel Functions NIPS 2010
Semi-Supervised Learning with Adversarially Missing Label Information NIPS 2010
Exploiting weakly-labeled Web images to improve object classification: a domain adaptation approach NIPS 2010
Humans Learn Using Manifolds, Reluctantly NIPS 2010