Optimization

Non-parametric Approximate Dynamic Programming via the Kernel Method NeurIPS 2012 Nonparametric Reduced Rank Regression NeurIPS 2012 No-Regret Algorithms for Unconstrained Online Convex Optimization NeurIPS 2012 Online L1-Dictionary Learning with Application to Novel Document Detection NeurIPS 2012 Online Learning in the Embedded Manifold of Low-rank Matrices JMLR 2012 Online Optimization with Gradual Variations COLT 2012 Online Submodular Minimization JMLR 2012 On the (Non-)existence of Convex, Calibrated Surrogate Losses for Ranking NeurIPS 2012 On the Structure of Nonlinearities in Pose Graph SLAM RSS 2012 On the Use of Non-Stationary Policies for Stationary Infinite-Horizon Markov Decision Processes NeurIPS 2012 Open Problem: Is Averaging Needed for Strongly Convex Stochastic Gradient Descent? COLT 2012 Optimal Distributed Online Prediction Using Mini-Batches JMLR 2012 Optimal Neural Tuning Curves for Arbitrary Stimulus Distributions: Discrimax, Infomax and Minimum L_p Loss NeurIPS 2012 Optimal Regularized Dual Averaging Methods for Stochastic Optimization NeurIPS 2012 Optimization of Temporal Dynamics for Adaptive Human-Robot Interaction in Assembly Manufacturing RSS 2012 Part & Clamp: Efficient Structured Output Learning AISTATS 2012 Perturbation based Large Margin Approach for Ranking AISTATS 2012 Positive Semidefinite Metric Learning Using Boosting-like Algorithms JMLR 2012 Practical Bayesian Optimization of Machine Learning Algorithms NeurIPS 2012 Practical Route Planning Under Delay Uncertainty: Stochastic Shortest Path Queries RSS 2012 Private Convex Empirical Risk Minimization and High-dimensional Regression COLT 2012 Provable ICA with Unknown Gaussian Noise, with Implications for Gaussian Mixtures and Autoencoders NeurIPS 2012 Proximal Newton-type methods for convex optimization NeurIPS 2012 Query Complexity of Derivative-Free Optimization NeurIPS 2012 Random Search for Hyper-Parameter Optimization JMLR 2012