Optimization

Fast recovery from a union of subspaces NeurIPS 2016 GenSVM: A Generalized Multiclass Support Vector Machine JMLR 2016 Hyperparameter optimization with approximate gradient ICML 2016 Learning from Multiway Data: Simple and Efficient Tensor Regression ICML 2016 Linearized Alternating Direction Method of Multipliers for Constrained Nonconvex Regularized Optimization ACML 2016 Local Minimax Complexity of Stochastic Convex Optimization NeurIPS 2016 Low-Rank Regression with Tensor Responses NeurIPS 2016 Maximizing Influence in an Ising Network: A Mean-Field Optimal Solution NeurIPS 2016 MOCCA: Mirrored Convex/Concave Optimization for Nonconvex Composite Functions JMLR 2016 Nested Mini-Batch K-Means NeurIPS 2016 Normalized Spectral Map Synchronization NeurIPS 2016 On Lloyd’s Algorithm: New Theoretical Insights for Clustering in Practice AISTATS 2016 On Lower and Upper Bounds in Smooth and Strongly Convex Optimization JMLR 2016 Optimal Black-Box Reductions Between Optimization Objectives NeurIPS 2016 Primal-Dual Rates and Certificates ICML 2016 Quadratic Optimization with Orthogonality Constraints: Explicit Lojasiewicz Exponent and Linear Convergence of Line-Search Methods ICML 2016 Regularized Nonlinear Acceleration NeurIPS 2016 Rounding-based Moves for Semi-Metric Labeling JMLR 2016 Scalable MAP inference in Bayesian networks based on a Map-Reduce approach PGM 2016 SDP Relaxation with Randomized Rounding for Energy Disaggregation NeurIPS 2016 Solving Random Systems of Quadratic Equations via Truncated Generalized Gradient Flow NeurIPS 2016 Sorting out typicality with the inverse moment matrix SOS polynomial NeurIPS 2016 Stochastic Discrete Clenshaw-Curtis Quadrature ICML 2016 Stochastic Optimization for Large-scale Optimal Transport NeurIPS 2016 Stochastic Variance Reduction for Nonconvex Optimization ICML 2016