Mathematics & Optimization

Robust Orthonormal Subspace Learning: Efficient Recovery of Corrupted Low-rank Matrices CVPR 2014 Robust Separation of Reflection from Multiple Images CVPR 2014 Robust Surface Reconstruction via Triple Sparsity CVPR 2014 Robust Tensor Decomposition with Gross Corruption NeurIPS 2014 Rounding-based Moves for Metric Labeling NeurIPS 2014 Saddle Points and Accelerated Perceptron Algorithms ICML 2014 SAGA: A Fast Incremental Gradient Method With Support for Non-Strongly Convex Composite Objectives NeurIPS 2014 Sample Complexity Bounds on Differentially Private Learning via Communication Complexity COLT 2014 Sampling for Inference in Probabilistic Models with Fast Bayesian Quadrature NeurIPS 2014 Scalable Kernel Methods via Doubly Stochastic Gradients NeurIPS 2014 Scalable Methods for Nonnegative Matrix Factorizations of Near-separable Tall-and-skinny Matrices NeurIPS 2014 Scalable Semidefinite Relaxation for Maximum A Posterior Estimation ICML 2014 Scale-space Processing Using Polynomial Representations CVPR 2014 Scaling Up Robust MDPs using Function Approximation ICML 2014 SCAMS: Simultaneous Clustering and Model Selection CVPR 2014 Scene Labeling Using Beam Search Under Mutex Constraints CVPR 2014 SeamSeg: Video Object Segmentation using Patch Seams CVPR 2014 Second-Order Shape Optimization for Geometric Inverse Problems in Vision CVPR 2014 Seeded Graph Matching for Correlated Erdos-Renyi Graphs JMLR 2014 Segmentation-Free Dynamic Scene Deblurring CVPR 2014 Semi-Separable Hamiltonian Monte Carlo for Inference in Bayesian Hierarchical Models NeurIPS 2014 Semi-Supervised Eigenvectors for Large-Scale Locally-Biased Learning JMLR 2014 Separable Kernel for Image Deblurring CVPR 2014 Sequential Convex Relaxation for Mutual Information-Based Unsupervised Figure-Ground Segmentation CVPR 2014 SerialRank: Spectral Ranking using Seriation NeurIPS 2014