Continuous Optimization

Riemannian Accelerated Gradient Methods via Extrapolation AISTATS 2023 Riemannian Projection-free Online Learning NeurIPS 2023 Riemannian stochastic optimization methods avoid strict saddle points NeurIPS 2023 Robust and Fast Measure of Information via Low-Rank Representation AAAI 2023 Robust High-Dimensional Low-Rank Matrix Estimation: Optimal Rate and Data-Adaptive Tuning JMLR 2023 Robust Matrix Sensing in the Semi-Random Model NeurIPS 2023 Robust Model Reasoning and Fitting via Dual Sparsity Pursuit NeurIPS 2023 Robust Second-Order Nonconvex Optimization and Its Application to Low Rank Matrix Sensing NeurIPS 2023 Saddle-to-Saddle Dynamics in Diagonal Linear Networks NeurIPS 2023 Safeguarded Learned Convex Optimization AAAI 2023 Safe Interval Path Planning with Kinodynamic Constraints AAAI 2023 Safety Verification of Nonlinear Systems with Bayesian Neural Network Controllers AAAI 2023 Sample Complexity Bound for Evaluating the Robust Observer’s Performance under Coprime Factors Uncertainty L4DC 2023 Sampling From a Schrödinger Bridge AISTATS 2023 SCADE: NeRFs from Space Carving With Ambiguity-Aware Depth Estimates CVPR 2023 Scalable and robust tensor ring decomposition for large-scale data UAI 2023 Scalable Bayesian Optimization Using Vecchia Approximations of Gaussian Processes AISTATS 2023 Scalable Bicriteria Algorithms for Non-Monotone Submodular Cover AISTATS 2023 Scalable Unbalanced Sobolev Transport for Measures on a Graph AISTATS 2023 Scale Invariant Power Iteration JMLR 2023 Searching for Optimal Per-Coordinate Step-sizes with Multidimensional Backtracking NeurIPS 2023 Second-Order Optimization with Lazy Hessians ICML 2023 Self-Adjusting Weighted Expected Improvement for Bayesian Optimization AutoML 2023 Self-Attention Amortized Distributional Projection Optimization for Sliced Wasserstein Point-Cloud Reconstruction ICML 2023 Self-Consistent Velocity Matching of Probability Flows NeurIPS 2023