convex optimization

Exploiting Strong Convexity from Data with Primal-Dual First-Order Algorithms ICML 2017 Faster and Non-ergodic O(1/K) Stochastic Alternating Direction Method of Multipliers NeurIPS 2017 Faster Coordinate Descent via Adaptive Importance Sampling AISTATS 2017 Fast Rates for Bandit Optimization with Upper-Confidence Frank-Wolfe NeurIPS 2017 Fast Stochastic Variance Reduced ADMM for Stochastic Composition Optimization IJCAI 2017 FFTLasso: Large-Scale LASSO in the Fourier Domain CVPR 2017 Following the Leader and Fast Rates in Online Linear Prediction: Curved Constraint Sets and Other Regularities JMLR 2017 Generalized Conditional Gradient for Sparse Estimation JMLR 2017 Geometric Descent Method for Convex Composite Minimization NeurIPS 2017 Geometry of 3D Environments and Sum of Squares Polynomials RSS 2017 GSOS: Gauss-Seidel Operator Splitting Algorithm for Multi-Term Nonsmooth Convex Composite Optimization ICML 2017 Improved Dynamic Regret for Non-degenerate Functions NeurIPS 2017 Input Convex Neural Networks ICML 2017 Large-Scale Quadratically Constrained Quadratic Program via Low-Discrepancy Sequences NeurIPS 2017 Linear Convergence of a Frank-Wolfe Type Algorithm over Trace-Norm Balls NeurIPS 2017 Multi-output Polynomial Networks and Factorization Machines NeurIPS 2017 Multiple Indefinite Kernel Learning for Feature Selection IJCAI 2017 Net-Trim: Convex Pruning of Deep Neural Networks with Performance Guarantee NeurIPS 2017 On Computationally Tractable Selection of Experiments in Measurement-Constrained Regression Models JMLR 2017 On Frank-Wolfe and Equilibrium Computation NeurIPS 2017 Online Learning with Local Permutations and Delayed Feedback ICML 2017 Online Summarization via Submodular and Convex Optimization CVPR 2017 Online to Offline Conversions, Universality and Adaptive Minibatch Sizes NeurIPS 2017 Optimal Algorithms for Smooth and Strongly Convex Distributed Optimization in Networks ICML 2017 Optimized Pre-Processing for Discrimination Prevention NeurIPS 2017