Multi-Task Learning

Reverse Multi-Label Learning NeurIPS 2010 Towards Holistic Scene Understanding: Feedback Enabled Cascaded Classification Models NeurIPS 2010 Asymptotically Optimal Regularization in Smooth Parametric Models NeurIPS 2009 Breaking Boundaries Between Induction Time and Diagnosis Time Active Information Acquisition NeurIPS 2009 Efficient and Accurate Lp-Norm Multiple Kernel Learning NeurIPS 2009 Evaluating multi-class learning strategies in a generative hierarchical framework for object detection NeurIPS 2009 Generalization Errors and Learning Curves for Regression with Multi-task Gaussian Processes NeurIPS 2009 Heterogeneous multitask learning with joint sparsity constraints NeurIPS 2009 Learning from Multiple Partially Observed Views - an Application to Multilingual Text Categorization NeurIPS 2009 Multi-Label Prediction via Sparse Infinite CCA NeurIPS 2009 Sharing Features among Dynamical Systems with Beta Processes NeurIPS 2009 When Is There a Representer Theorem? Vector Versus Matrix Regularizers JMLR 2009 Who’s Doing What: Joint Modeling of Names and Verbs for Simultaneous Face and Pose Annotation NeurIPS 2009 Cascaded Classification Models: Combining Models for Holistic Scene Understanding NeurIPS 2008 Clustered Multi-Task Learning: A Convex Formulation NeurIPS 2008 Multi-task Gaussian Process Learning of Robot Inverse Dynamics NeurIPS 2008 Simple Local Models for Complex Dynamical Systems NeurIPS 2008 Sparse Convolved Gaussian Processes for Multi-output Regression NeurIPS 2008 A Spectral Regularization Framework for Multi-Task Structure Learning NeurIPS 2007 A Stochastic Algorithm for Feature Selection in Pattern Recognition JMLR 2007 Multi-task Gaussian Process Prediction NeurIPS 2007 Multi-Task Learning for Classification with Dirichlet Process Priors JMLR 2007 Multi-Task Learning via Conic Programming NeurIPS 2007 Semi-Supervised Multitask Learning NeurIPS 2007 Boosting Structured Prediction for Imitation Learning NeurIPS 2006