Learning Paradigms

Distributed Estimation, Information Loss and Exponential Families NeurIPS 2014 Learning to Learn, from Transfer Learning to Domain Adaptation: A Unifying Perspective CVPR 2014 Linear and Parallel Learning of Markov Random Fields ICML 2014 PAC-inspired Option Discovery in Lifelong Reinforcement Learning ICML 2014 Self-Paced Learning with Diversity NeurIPS 2014 Optimizing Instructional Policies NeurIPS 2013 Self-Paced Learning for Long-Term Tracking CVPR 2013 A Case Study on Meta-Generalising: A Gaussian Processes Approach JMLR 2012 A Differentially Private Stochastic Gradient Descent Algorithm for Multiparty Classification AISTATS 2012 Bayesian Hierarchical Reinforcement Learning NeurIPS 2012 Distributed Learning, Communication Complexity and Privacy COLT 2012 Distributed Probabilistic Learning for Camera Networks with Missing Data NeurIPS 2012 Practical Bayesian Optimization of Machine Learning Algorithms NeurIPS 2012 Protocols for Learning Classifiers on Distributed Data AISTATS 2012 How Do Humans Teach: On Curriculum Learning and Teaching Dimension NeurIPS 2011 Learning to Learn with Compound HD Models NeurIPS 2011 Online Learning: Beyond Regret COLT 2011 Constructing Skill Trees for Reinforcement Learning Agents from Demonstration Trajectories NeurIPS 2010 Graph-Valued Regression NeurIPS 2010 Multiparty Differential Privacy via Aggregation of Locally Trained Classifiers NeurIPS 2010 On Herding and the Perceptron Cycling Theorem NeurIPS 2010 Reinforcement Learning to adjust Robot Movements to New Situations RSS 2010 Self-Paced Learning for Latent Variable Models NeurIPS 2010 Evolutionary Model Type Selection for Global Surrogate Modeling JMLR 2009 Asynchronous Distributed Learning of Topic Models NeurIPS 2008