Learning Theory

Learning Halfspaces Under Log-Concave Densities: Polynomial Approximations and Moment Matching COLT 2013 Learning Kernels Using Local Rademacher Complexity NeurIPS 2013 Learning Theory Analysis for Association Rules and Sequential Event Prediction JMLR 2013 Learning Trees from Strings: A Strong Learning Algorithm for some Context-Free Grammars JMLR 2013 Learning Triggering Kernels for Multi-dimensional Hawkes Processes ICML 2013 Learning Using Local Membership Queries COLT 2013 Learning with Noisy Labels NeurIPS 2013 Localization and Adaptation in Online Learning AISTATS 2013 Lower Bounds and Selectivity of Weak-Consistent Policies in Stochastic Multi-Armed Bandit Problem JMLR 2013 Machine Learning with Operational Costs JMLR 2013 Manifold Regularization and Semi-supervised Learning: Some Theoretical Analyses JMLR 2013 Matrix factorization with binary components NeurIPS 2013 Minimax Optimal Algorithms for Unconstrained Linear Optimization NeurIPS 2013 Minimax Theory for High-dimensional Gaussian Mixtures with Sparse Mean Separation NeurIPS 2013 Moment-based Uniform Deviation Bounds for k-means and Friends NeurIPS 2013 More data speeds up training time in learning halfspaces over sparse vectors NeurIPS 2013 Near-optimal Batch Mode Active Learning and Adaptive Submodular Optimization ICML 2013 Near-Optimal Bounds for Cross-Validation via Loss Stability ICML 2013 On Flat versus Hierarchical Classification in Large-Scale Taxonomies NeurIPS 2013 Online learning in episodic Markovian decision processes by relative entropy policy search NeurIPS 2013 Online Learning under Delayed Feedback ICML 2013 On model selection consistency of penalized M-estimators: a geometric theory NeurIPS 2013 On the Asymptotic Optimality of Maximum Margin Bayesian Networks AISTATS 2013 On the Complexity of Bandit and Derivative-Free Stochastic Convex Optimization COLT 2013 On the difficulty of training recurrent neural networks ICML 2013