Mathematics & Optimization

Lifelong Optimization with Low Regret AISTATS 2019 Lifted Hinge-Loss Markov Random Fields AAAI 2019 Lifted Message Passing for Hybrid Probabilistic Inference IJCAI 2019 Lifted Proximal Operator Machines AAAI 2019 Lifting high-dimensional non-linear models with Gaussian regressors AISTATS 2019 Lifting Vectorial Variational Problems: A Natural Formulation Based on Geometric Measure Theory and Discrete Exterior Calculus CVPR 2019 Limitations of the empirical Fisher approximation for natural gradient descent NeurIPS 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 Linear Discriminant Differential Evolution for Feature Selection in Emotional Speech Recognition Interspeech 2019 Linear Kernel Tests via Empirical Likelihood for High-Dimensional Data AAAI 2019 Linearly Converging Quasi Branch and Bound Algorithms for Global Rigid Registration ICCV 2019 Linear Stochastic Bandits Under Safety Constraints NeurIPS 2019 Lipschitz Adaptivity with Multiple Learning Rates in Online Learning COLT 2019 List-decodable Linear Regression NeurIPS 2019 Local Koopman Operators for Data-Driven Control of Robotic Systems RSS 2019 Locally Private Gaussian Estimation NeurIPS 2019 Locally Private Learning without Interaction Requires Separation NeurIPS 2019 Locally Private Mean Estimation: Z-test and Tight Confidence Intervals AISTATS 2019 Local Regularization of Noisy Point Clouds: Improved Global Geometric Estimates and Data Analysis JMLR 2019 Local Saddle Point Optimization: A Curvature Exploitation Approach AISTATS 2019 Local Search with Efficient Automatic Configuration for Minimum Vertex Cover IJCAI 2019 Local SGD with Periodic Averaging: Tighter Analysis and Adaptive Synchronization NeurIPS 2019 Logarithmic Regret for Online Control NeurIPS 2019 Logarithmic Regret for Online Gradient Descent Beyond Strong Convexity AISTATS 2019