Optimization

A Smoothed Approximate Linear Program NeurIPS 2009 Asymptotically Optimal Regularization in Smooth Parametric Models NeurIPS 2009 Asymptotic Analysis of MAP Estimation via the Replica Method and Compressed Sensing NeurIPS 2009 AUC optimization and the two-sample problem NeurIPS 2009 Beyond Convexity: Online Submodular Minimization NeurIPS 2009 Bi-Level Path Following for Cross Validated Solution of Kernel Quantile Regression JMLR 2009 Breaking Boundaries Between Induction Time and Diagnosis Time Active Information Acquisition NeurIPS 2009 Classification with Gaussians and Convex Loss JMLR 2009 Convex Relaxation of Mixture Regression with Efficient Algorithms NeurIPS 2009 Data-driven calibration of linear estimators with minimal penalties NeurIPS 2009 Directed Regression NeurIPS 2009 Dual Averaging Method for Regularized Stochastic Learning and Online Optimization NeurIPS 2009 DUOL: A Double Updating Approach for Online Learning NeurIPS 2009 Efficient and Accurate Lp-Norm Multiple Kernel Learning NeurIPS 2009 Efficient Bregman Range Search NeurIPS 2009 Efficient Large-Scale Distributed Training of Conditional Maximum Entropy Models NeurIPS 2009 Efficient Learning using Forward-Backward Splitting NeurIPS 2009 Efficient Online and Batch Learning Using Forward Backward Splitting JMLR 2009 Efficient Recovery of Jointly Sparse Vectors NeurIPS 2009 Ensemble Nystrom Method NeurIPS 2009 Entropic Graph Regularization in Non-Parametric Semi-Supervised Classification NeurIPS 2009 Evolutionary Model Type Selection for Global Surrogate Modeling JMLR 2009 Fast Graph Laplacian Regularized Kernel Learning via Semidefinite–Quadratic–Linear Programming NeurIPS 2009 Grouped Orthogonal Matching Pursuit for Variable Selection and Prediction NeurIPS 2009 Heavy-Tailed Symmetric Stochastic Neighbor Embedding NeurIPS 2009