Continuous Optimization

Incomplete Label Multi-Task Deep Learning for Spatio-Temporal Event Subtype Forecasting AAAI 2019 Interior-Point Methods Strike Back: Solving the Wasserstein Barycenter Problem NeurIPS 2019 Interpolating between Optimal Transport and MMD using Sinkhorn Divergences AISTATS 2019 Inverse Path Tracing for Joint Material and Lighting Estimation CVPR 2019 Isospectralization, or How to Hear Shape, Style, and Correspondence CVPR 2019 Iterative Linearized Control: Stable Algorithms and Complexity Guarantees ICML 2019 Jointly Multiple Hash Learning AAAI 2019 Katalyst: Boosting Convex Katayusha for Non-Convex Problems with a Large Condition Number ICML 2019 Large-scale optimal transport map estimation using projection pursuit NeurIPS 2019 Large-Scale Sparse Kernel Canonical Correlation Analysis ICML 2019 Lazifying Conditional Gradient Algorithms JMLR 2019 Learning to Match via Inverse Optimal Transport JMLR 2019 Learning to Optimize in Swarms NeurIPS 2019 Learning Weighted Top-k Support Vector Machine ACML 2019 Least Squares Estimation of Weakly Convex Functions AISTATS 2019 Less but Better: Generalization Enhancement of Ordinal Embedding via Distributional Margin AAAI 2019 Lifted Hinge-Loss Markov Random Fields AAAI 2019 Lifted Proximal Operator Machines AAAI 2019 Lifting high-dimensional non-linear models with Gaussian regressors AISTATS 2019 Linear-Complexity Data-Parallel Earth Mover’s Distance Approximations ICML 2019 Linear Convergence of the Primal-Dual Gradient Method for Convex-Concave Saddle Point Problems without Strong Convexity AISTATS 2019 Linearly Converging Quasi Branch and Bound Algorithms for Global Rigid Registration ICCV 2019 Local Saddle Point Optimization: A Curvature Exploitation Approach AISTATS 2019 Lower Bounds for Parallel and Randomized Convex Optimization COLT 2019 Lower Bounds for Smooth Nonconvex Finite-Sum Optimization ICML 2019