second-order optimization

Beyond the Mean: Fisher-Orthogonal Projection for Natural Gradient Descent in Large Batch Training AAAI 2026 Faster Newton Methods for Convex and Nonconvex Optimization in Gradient Complexity COLT 2026 FedPM: Federated Learning Using Second-order Optimization with Preconditioned Mixing of Local Parameters AAAI 2026 AdaFisher: Adaptive Second Order Optimization via Fisher Information ICLR 2025 A New Perspective on Shampoo's Preconditioner ICLR 2025 Debiasing Mini-Batch Quadratics for Applications in Deep Learning ICLR 2025 Fast Second-Order Online Kernel Learning Through Incremental Matrix Sketching and Decomposition IJCAI 2025 Global curvature for second-order optimization of neural networks ICML 2025 Hessian-Free Online Certified Unlearning ICLR 2025 How Well Can Transformers Emulate In-Context Newton’s Method? AISTATS 2025 Lacuna Inc. at SemEval-2025 Task 4: LoRA-Enhanced Influence-Based Unlearning for LLMs SemEval 2025 Newton Meets Marchenko-Pastur: Massively Parallel Second-Order Optimization with Hessian Sketching and Debiasing ICLR 2025 On Adaptive Stochastic Optimization for Streaming Data: A Newton's Method with O(dN) Operations JMLR 2025 Preserving Deep Representations in One-Shot Pruning: A Hessian-Free Second-Order Optimization Framework ICLR 2025 Unleashing High-Quality Image Generation in Diffusion Sampling Using Second-Order Levenberg-Marquardt-Langevin ICCV 2025 A Layer-Wise Natural Gradient Optimizer for Training Deep Neural Networks NeurIPS 2024 Black Box Variational Inference with a Deterministic Objective: Faster, More Accurate, and Even More Black Box JMLR 2024 Communication Efficient Distributed Newton Method over Unreliable Networks AAAI 2024 Exact, Tractable Gauss-Newton Optimization in Deep Reversible Architectures Reveal Poor Generalization NeurIPS 2024 FOSI: Hybrid First and Second Order Optimization ICLR 2024 Identifying Policy Gradient Subspaces ICLR 2024 Kronecker-Factored Approximate Curvature for Physics-Informed Neural Networks NeurIPS 2024 Krylov Cubic Regularized Newton: A Subspace Second-Order Method with Dimension-Free Convergence Rate AISTATS 2024 Newton Losses: Using Curvature Information for Learning with Differentiable Algorithms NeurIPS 2024 On the Parameterization of Second-Order Optimization Effective towards the Infinite Width ICLR 2024