Multi-Task Learning

Learning curves for multi-task Gaussian process regression NeurIPS 2012 Learning Multiple Tasks using Shared Hypotheses NeurIPS 2012 Learning Partially Observable Models Using Temporally Abstract Decision Trees NeurIPS 2012 Lifted coordinate descent for learning with trace-norm regularization AISTATS 2012 Marginal Regression For Multitask Learning AISTATS 2012 Max-Margin Structured Output Regression for Spatio-Temporal Action Localization NeurIPS 2012 Minimax Multi-Task Learning and a Generalized Loss-Compositional Paradigm for MTL NeurIPS 2012 Monte Carlo Methods for Maximum Margin Supervised Topic Models NeurIPS 2012 Multiple Choice Learning: Learning to Produce Multiple Structured Outputs NeurIPS 2012 Multiple Operator-valued Kernel Learning NeurIPS 2012 Multi-Stage Multi-Task Feature Learning NeurIPS 2012 Multi-Task Averaging NeurIPS 2012 Multi-task Vector Field Learning NeurIPS 2012 Multi-view Positive and Unlabeled Learning ACML 2012 On Triangular versus Edge Representations --- Towards Scalable Modeling of Networks NeurIPS 2012 Part & Clamp: Efficient Structured Output Learning AISTATS 2012 Putting Bayes to sleep NeurIPS 2012 Robust Multi-task Regression with Grossly Corrupted Observations AISTATS 2012 Simultaneously Leveraging Output and Task Structures for Multiple-Output Regression NeurIPS 2012 SpeedBoost: Anytime Prediction with Uniform Near-Optimality AISTATS 2012 Assisting Main Task Learning by Heterogeneous Auxiliary Tasks with Applications to Skin Cancer Screening AISTATS 2011 Clustered Multi-Task Learning Via Alternating Structure Optimization NeurIPS 2011 Co-Training for Domain Adaptation NeurIPS 2011 Deep Learners Benefit More from Out-of-Distribution Examples AISTATS 2011 Generalizing from Several Related Classification Tasks to a New Unlabeled Sample NeurIPS 2011