Active Learning

Gaussian Process Preference Elicitation NeurIPS 2010 Guarantees for Approximate Incremental SVMs AISTATS 2010 Hashing Hyperplane Queries to Near Points with Applications to Large-Scale Active Learning NeurIPS 2010 Multi-View Active Learning in the Non-Realizable Case NeurIPS 2010 Near-Optimal Bayesian Active Learning with Noisy Observations NeurIPS 2010 Negative Results for Active Learning with Convex Losses AISTATS 2010 On the Foundations of Noise-free Selective Classification JMLR 2010 Rademacher Complexities and Bounding the Excess Risk in Active Learning JMLR 2010 Self-Paced Learning for Latent Variable Models NeurIPS 2010 Supervised Clustering NeurIPS 2010 Trading off Mistakes and Don't-Know Predictions NeurIPS 2010 Accelerated Gradient Methods for Stochastic Optimization and Online Learning NeurIPS 2009 Adaptive Design Optimization in Experiments with People NeurIPS 2009 Adaptive Regularization of Weight Vectors NeurIPS 2009 Analysis of Perceptron-Based Active Learning JMLR 2009 Breaking Boundaries Between Induction Time and Diagnosis Time Active Information Acquisition NeurIPS 2009 DUOL: A Double Updating Approach for Online Learning NeurIPS 2009 Identification of Recurrent Neural Networks by Bayesian Interrogation Techniques JMLR 2009 Learning to Explore and Exploit in POMDPs NeurIPS 2009 Noisy Generalized Binary Search NeurIPS 2009 Submodularity Cuts and Applications NeurIPS 2009 Sufficient Conditions for Agnostic Active Learnable NeurIPS 2009 Active Learning by Spherical Subdivision JMLR 2008 Active Learning of Causal Networks with Intervention Experiments and Optimal Designs JMLR 2008 Adaptive Martingale Boosting NeurIPS 2008