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Weakly Supervised Learning

3895 directly classified papers

Papers per year

Papers

Ranking annotators for crowdsourced labeling tasks NIPS 2011
Unsupervised Supervised Learning II: Margin-Based Classification Without Labels JMLR 2011
Learning from Partial Labels JMLR 2011
A Theory of Multiclass Boosting NIPS 2010
Convex Multiple-Instance Learning by Estimating Likelihood Ratio NIPS 2010
Learning via Gaussian Herding NIPS 2010
Multitask Learning without Label Correspondences NIPS 2010
Exploiting weakly-labeled Web images to improve object classification: a domain adaptation approach NIPS 2010
A Reduction from Apprenticeship Learning to Classification NIPS 2010
Simultaneous Object Detection and Ranking with Weak Supervision NIPS 2010
A Discriminative Latent Model of Image Region and Object Tag Correspondence NIPS 2010
Avoiding False Positive in Multi-Instance Learning NIPS 2010
Multiclass-Multilabel Classification with More Classes than Examples AISTATS 2010
Generalized Expectation Criteria for Semi-Supervised Learning with Weakly Labeled Data JMLR 2010
Modeling annotator expertise: Learning when everybody knows a bit of something AISTATS 2010
Learning From Crowds JMLR 2010
MOA: Massive Online Analysis JMLR 2010
Feature Selection using Multiple Streams AISTATS 2010
Posterior Regularization for Structured Latent Variable Models JMLR 2010
Supervised Clustering NIPS 2010
Reducing Label Complexity by Learning From Bags AISTATS 2010
Learning from Candidate Labeling Sets NIPS 2010
Efficient Heuristics for Discriminative Structure Learning of Bayesian Network Classifiers JMLR 2010
Supervised Descriptive Rule Discovery: A Unifying Survey of Contrast Set, Emerging Pattern and Subgroup Mining JMLR 2009
Using Local Dependencies within Batches to Improve Large Margin Classifiers JMLR 2009