Optimization

Reconstruction from Anisotropic Random Measurements COLT 2012 Recovery of Sparse Probability Measures via Convex Programming NeurIPS 2012 Regularization Paths with Guarantees for Convex Semidefinite Optimization AISTATS 2012 Regularization Techniques for Learning with Matrices JMLR 2012 Regularized Bundle Methods for Convex and Non-Convex Risks JMLR 2012 Regularized Off-Policy TD-Learning NeurIPS 2012 Relax and Randomize : From Value to Algorithms NeurIPS 2012 Risk Aversion in Markov Decision Processes via Near Optimal Chernoff Bounds NeurIPS 2012 Robust Loop Closing Over Time RSS 2012 Robustness and risk-sensitivity in Markov decision processes NeurIPS 2012 Sampling Methods for the Nyström Method JMLR 2012 Scalable nonconvex inexact proximal splitting NeurIPS 2012 Scaled Gradients on Grassmann Manifolds for Matrix Completion NeurIPS 2012 Scaling MPE Inference for Constrained Continuous Markov Random Fields with Consensus Optimization NeurIPS 2012 Selective Labeling via Error Bound Minimization NeurIPS 2012 Simultaneously Leveraging Output and Task Structures for Multiple-Output Regression NeurIPS 2012 Smoothing Multivariate Performance Measures JMLR 2012 Smooth-projected Neighborhood Pursuit for High-dimensional Nonparanormal Graph Estimation NeurIPS 2012 Sparse Additive Machine AISTATS 2012 Sparse and Unique Nonnegative Matrix Factorization Through Data Preprocessing JMLR 2012 Sparse Prediction with the k-Support Norm NeurIPS 2012 Sparsistency of the Edge Lasso over Graphs AISTATS 2012 Spectral Learning of General Weighted Automata via Constrained Matrix Completion NeurIPS 2012 SpeedBoost: Anytime Prediction with Uniform Near-Optimality AISTATS 2012 Statistical Optimization in High Dimensions AISTATS 2012