Learning Theory

Multiclass Learning with Simplex Coding NeurIPS 2012 Multi-Instance Learning with Any Hypothesis Class JMLR 2012 New Bounds for Learning Intervals with Implications for Semi-Supervised Learning COLT 2012 No Internal Regret via Neighborhood Watch AISTATS 2012 Non-parametric Approximate Dynamic Programming via the Kernel Method NeurIPS 2012 No-Regret Algorithms for Unconstrained Online Convex Optimization NeurIPS 2012 Nyström Method vs Random Fourier Features: A Theoretical and Empirical Comparison NeurIPS 2012 On Estimation and Selection for Topic Models AISTATS 2012 Online Regret Bounds for Undiscounted Continuous Reinforcement Learning NeurIPS 2012 Online Submodular Minimization JMLR 2012 On Multilabel Classification and Ranking with Partial Feedback NeurIPS 2012 On Ranking and Generalization Bounds JMLR 2012 On the Convergence Rate of -Norm Multiple Kernel Learning JMLR 2012 On the Necessity of Irrelevant Variables JMLR 2012 On the (Non-)existence of Convex, Calibrated Surrogate Losses for Ranking NeurIPS 2012 On the Sample Complexity of Robust PCA NeurIPS 2012 Optimal Regularized Dual Averaging Methods for Stochastic Optimization NeurIPS 2012 Pointwise Tracking the Optimal Regression Function NeurIPS 2012 Privacy Aware Learning NeurIPS 2012 Query Complexity of Derivative-Free Optimization NeurIPS 2012 Random Design Analysis of Ridge Regression COLT 2012 Random Feature Maps for Dot Product Kernels AISTATS 2012 Random Search for Hyper-Parameter Optimization JMLR 2012 Relax and Randomize : From Value to Algorithms NeurIPS 2012 Risk-Aversion in Multi-armed Bandits NeurIPS 2012