newton's method

Instability, Computational Efficiency and Statistical Accuracy JMLR 2025 On Adaptive Stochastic Optimization for Streaming Data: A Newton's Method with O(dN) Operations JMLR 2025 Statistical Inference of Constrained Stochastic Optimization via Sketched Sequential Quadratic Programming JMLR 2025 Transformers Learn to Achieve Second-Order Convergence Rates for In-Context Linear Regression NeurIPS 2024 Faster Differentially Private Convex Optimization via Second-Order Methods NeurIPS 2023 ISAAC Newton: Input-based Approximate Curvature for Newton's Method ICLR 2023 One-step differentiation of iterative algorithms NeurIPS 2023 Accelerating Adaptive Cubic Regularization of Newton's Method via Random Sampling JMLR 2022 EiGLasso for Scalable Sparse Kronecker-Sum Inverse Covariance Estimation JMLR 2022 Optimal and Adaptive Monteiro-Svaiter Acceleration NeurIPS 2022 Communication-Efficient Distributed Optimization with Quantized Preconditioners ICML 2021 Distributed estimation of the inverse Hessian by determinantal averaging NeurIPS 2019 Convergence of Cubic Regularization for Nonconvex Optimization under KL Property NeurIPS 2018 The Physical Systems Behind Optimization Algorithms NeurIPS 2018 QUIC: Quadratic Approximation for Sparse Inverse Covariance Estimation JMLR 2014 Sparse Inverse Covariance Matrix Estimation Using Quadratic Approximation NeurIPS 2011