quasi-newton method

Opt3DGS: Optimizing 3D Gaussian Splatting with Adaptive Exploration and Curvature-Aware Exploitation AAAI 2026 On Adaptive Stochastic Optimization for Streaming Data: A Newton's Method with O(dN) Operations JMLR 2025 qNBO: quasi-Newton Meets Bilevel Optimization ICLR 2025 The Sparse-Plus-Low-Rank Quasi-Newton Method for Entropic-Regularized Optimal Transport ICML 2025 Adaptive Quasi-Newton and Anderson Acceleration Framework with Explicit Global (Accelerated) Convergence Rates AISTATS 2024 Exploring Jacobian Inexactness in Second-Order Methods for Variational Inequalities: Lower Bounds, Optimal Algorithms and Quasi-Newton Approximations NeurIPS 2024 Incremental Quasi-Newton Methods with Faster Superlinear Convergence Rates AAAI 2024 QN-Mixer: A Quasi-Newton MLP-Mixer Model for Sparse-View CT Reconstruction CVPR 2024 Quantum Algorithm for Online Exp-concave Optimization ICML 2024 Sample Average Approximation for Black-Box Variational Inference UAI 2024 Sharpened Lazy Incremental Quasi-Newton Method AISTATS 2024 Towards Scalable and Stable Parallelization of Nonlinear RNNs NeurIPS 2024 Accelerated Quasi-Newton Proximal Extragradient: Faster Rate for Smooth Convex Optimization NeurIPS 2023 Block Broyden's Methods for Solving Nonlinear Equations NeurIPS 2023 Online Learning Guided Curvature Approximation: A Quasi-Newton Method with Global Non-Asymptotic Superlinear Convergence COLT 2023 Quasi-Newton Steps for Efficient Online Exp-Concave Optimization COLT 2023 Sequential Gradient Descent and Quasi-Newton’s Method for Change-Point Analysis AISTATS 2023 A Stochastic Momentum Accelerated Quasi-Newton Method for Neural Networks (Student Abstract) AAAI 2022 A Variant of Anderson Mixing with Minimal Memory Size NeurIPS 2022 Explicit Convergence Rates of Greedy and Random Quasi-Newton Methods JMLR 2022 Fast Bayesian Coresets via Subsampling and Quasi-Newton Refinement NeurIPS 2022 On the Practical Robustness of the Nesterov’s Accelerated Quasi-Newton Method AAAI 2022 Quasi-Newton Methods for Saddle Point Problems NeurIPS 2022 Sharpened Quasi-Newton Methods: Faster Superlinear Rate and Larger Local Convergence Neighborhood ICML 2022 SHINE: SHaring the INverse Estimate from the forward pass for bi-level optimization and implicit models ICLR 2022