convex optimization

Provable Variational Inference for Constrained Log-Submodular Models NeurIPS 2018 Quadratic Decomposable Submodular Function Minimization NeurIPS 2018 Randomized Block Cubic Newton Method ICML 2018 Ring Loss: Convex Feature Normalization for Face Recognition CVPR 2018 RSG: Beating Subgradient Method without Smoothness and Strong Convexity JMLR 2018 Saturating Splines and Feature Selection JMLR 2018 Scalable Laplacian K-modes NeurIPS 2018 Short-term Sparse Portfolio Optimization Based on Alternating Direction Method of Multipliers JMLR 2018 Smooth and Sparse Optimal Transport AISTATS 2018 Solving Non-smooth Constrained Programs with Lower Complexity than O(1/ε): A Primal-Dual Homotopy Smoothing Approach NeurIPS 2018 Solving Separable Nonsmooth Problems Using Frank-Wolfe with Uniform Affine Approximations IJCAI 2018 SoS-RSC: A Sum-of-Squares Polynomial Approach to Robustifying Subspace Clustering Algorithms CVPR 2018 Stochastic Composite Mirror Descent: Optimal Bounds with High Probabilities NeurIPS 2018 Stochastic PCA with ℓ_2 and ℓ_1 Regularization ICML 2018 Stochastic Three-Composite Convex Minimization with a Linear Operator AISTATS 2018 Stochastic Zeroth-order Optimization in High Dimensions AISTATS 2018 Theoretical Analysis of Sparse Subspace Clustering with Missing Entries ICML 2018 The Pessimistic Limits and Possibilities of Margin-based Losses in Semi-supervised Learning NeurIPS 2018 ThunderSVM: A Fast SVM Library on GPUs and CPUs JMLR 2018 TRAINING GENERATIVE ADVERSARIAL NETWORKS VIA PRIMAL-DUAL SUBGRADIENT METHODS: A LAGRANGIAN PERSPECTIVE ON GAN ICLR 2018 Unleashing Linear Optimizers for Group-Fair Learning and Optimization COLT 2018 Weighted SGD for ℓ_p Regression with Randomized Preconditioning JMLR 2018 Accelerated Doubly Stochastic Gradient Algorithm for Large-scale Empirical Risk Minimization IJCAI 2017 Accelerated First-order Methods for Geodesically Convex Optimization on Riemannian Manifolds NeurIPS 2017 Adaptive Clustering through Semidefinite Programming NeurIPS 2017