Optimization

Extrinsic Calibration from Per-Sensor Egomotion RSS 2012 Factoring nonnegative matrices with linear programs NeurIPS 2012 Fast, Exact Model Selection and Permutation Testing for l2-Regularized Logistic Regression AISTATS 2012 Fast interior-point inference in high-dimensional sparse, penalized state-space models AISTATS 2012 Fast Learning Rate of Multiple Kernel Learning: Trade-Off between Sparsity and Smoothness AISTATS 2012 Fast Variational Bayesian Inference for Non-Conjugate Matrix Factorization Models AISTATS 2012 Fast Variational Inference in the Conjugate Exponential Family NeurIPS 2012 Feature Clustering for Accelerating Parallel Coordinate Descent NeurIPS 2012 Finding Exemplars from Pairwise Dissimilarities via Simultaneous Sparse Recovery NeurIPS 2012 Finite Sample Convergence Rates of Zero-Order Stochastic Optimization Methods NeurIPS 2012 Forging The Graphs: A Low Rank and Positive Semidefinite Graph Learning Approach NeurIPS 2012 Forward Basis Selection for Sparse Approximation over Dictionary AISTATS 2012 Fused sparsity and robust estimation for linear models with unknown variance NeurIPS 2012 GenDeR: A Generic Diversified Ranking Algorithm NeurIPS 2012 Generalized Optimal Reverse Prediction AISTATS 2012 Generic Methods for Optimization-Based Modeling AISTATS 2012 Globally Convergent Dual MAP LP Relaxation Solvers using Fenchel-Young Margins NeurIPS 2012 Gradient-based kernel method for feature extraction and variable selection NeurIPS 2012 Hamming Distance Metric Learning NeurIPS 2012 Hierarchical Optimistic Region Selection driven by Curiosity NeurIPS 2012 Infinite-Dimensional Kalman Filtering Approach to Spatio-Temporal Gaussian Process Regression AISTATS 2012 Interpreting prediction markets: a stochastic approach NeurIPS 2012 Isotropic Hashing NeurIPS 2012 Iterative Reweighted Algorithms for Matrix Rank Minimization JMLR 2012 Iterative Thresholding Algorithm for Sparse Inverse Covariance Estimation NeurIPS 2012