optimization algorithm

Achieving High Accuracy with PINNs via Energy Natural Gradient Descent ICML 2023 A Fast Optimistic Method for Monotone Variational Inequalities ICML 2023 Datasets and Benchmarks for Nanophotonic Structure and Parametric Design Simulations NeurIPS 2023 Does It Pay to Optimize AUC? AAAI 2023 Finding an ϵ-Close Minimal Variation of Parameters in Bayesian Networks IJCAI 2023 PAC-Bayesian Learning of Optimization Algorithms AISTATS 2023 Policy Gradient in Robust MDPs with Global Convergence Guarantee ICML 2023 Symbolic Discovery of Optimization Algorithms NeurIPS 2023 Symmetry-Aware Robot Design with Structured Subgroups ICML 2023 The Bayesian Learning Rule JMLR 2023 Tilted Sparse Additive Models ICML 2023 Towards Constituting Mathematical Structures for Learning to Optimize ICML 2023 Transformer-Based Learned Optimization CVPR 2023 Accelerated Projected Gradient Algorithms for Sparsity Constrained Optimization Problems NeurIPS 2022 A Contraction Theory Approach to Optimization Algorithms from Acceleration Flows AISTATS 2022 Adaptive Inertia: Disentangling the Effects of Adaptive Learning Rate and Momentum ICML 2022 A Momentumized, Adaptive, Dual Averaged Gradient Method JMLR 2022 Anytime Capacity Expansion in Medical Residency Match by Monte Carlo Tree Search IJCAI 2022 A Variant of Anderson Mixing with Minimal Memory Size NeurIPS 2022 Breaking the Convergence Barrier: Optimization via Fixed-Time Convergent Flows AAAI 2022 Deep Networks on Toroids: Removing Symmetries Reveals the Structure of Flat Regions in the Landscape Geometry ICML 2022 Differentially Private Coordinate Descent for Composite Empirical Risk Minimization ICML 2022 Do Current Multi-Task Optimization Methods in Deep Learning Even Help? NeurIPS 2022 Domain Representative Keywords Selection: A Probabilistic Approach ACL 2022 Efficient Algorithms for Monotone Non-Submodular Maximization with Partition Matroid Constraint IJCAI 2022