Theory

Composite Multiclass Losses NeurIPS 2011 Discussion of “A conditional game for comparing approximations” AISTATS 2011 Discussion of “Learning Equivalence Classes of Acyclic Models with Latent and Selection Variables from Multiple Datasets with Overlapping Variables” AISTATS 2011 Does an Efficient Calibrated Forecasting Strategy Exist? COLT 2011 Efficient Learning of Generalized Linear and Single Index Models with Isotonic Regression NeurIPS 2011 Error Analysis of Laplacian Eigenmaps for Semi-supervised Learning AISTATS 2011 Expressive Power and Approximation Errors of Restricted Boltzmann Machines NeurIPS 2011 Finite Time Analysis of Stratified Sampling for Monte Carlo NeurIPS 2011 How biased are maximum entropy models? NeurIPS 2011 Improved Loss Bounds For Multiple Kernel Learning AISTATS 2011 Learning in Hilbert vs. Banach Spaces: A Measure Embedding Viewpoint NeurIPS 2011 Learning with the weighted trace-norm under arbitrary sampling distributions NeurIPS 2011 Locally Defined Principal Curves and Surfaces JMLR 2011 Minimax Localization of Structural Information in Large Noisy Matrices NeurIPS 2011 Noise Thresholds for Spectral Clustering NeurIPS 2011 Online Learning: Beyond Regret COLT 2011 Online Learning in Case of Unbounded Losses Using Follow the Perturbed Leader Algorithm JMLR 2011 Oracle inequalities for computationally budgeted model selection COLT 2011 Scalable Training of Mixture Models via Coresets NeurIPS 2011 Selecting the State-Representation in Reinforcement Learning NeurIPS 2011 Shallow vs. Deep Sum-Product Networks NeurIPS 2011 Spectral Methods for Learning Multivariate Latent Tree Structure NeurIPS 2011 Statistical Performance of Convex Tensor Decomposition NeurIPS 2011 The Fast Convergence of Boosting NeurIPS 2011 The Local Rademacher Complexity of Lp-Norm Multiple Kernel Learning NeurIPS 2011