hessian matrix

A Two-Level Decomposition Framework Exploiting First and Second Order Information for SVM Training Problems JMLR 2021 Newton-LESS: Sparsification without Trade-offs for the Sketched Newton Update NeurIPS 2021 Non-PSD matrix sketching with applications to regression and optimization UAI 2021 Analytic Characterization of the Hessian in Shallow ReLU Models: A Tale of Symmetry NeurIPS 2020 Approximate Cross-Validation with Low-Rank Data in High Dimensions NeurIPS 2020 Assessing Local Generalization Capability in Deep Models AISTATS 2020 Detecting Extrapolation with Local Ensembles ICLR 2020 On the interplay between noise and curvature and its effect on optimization and generalization AISTATS 2020 On the linearity of large non-linear models: when and why the tangent kernel is constant NeurIPS 2020 Collaborative Channel Pruning for Deep Networks ICML 2019 Adaptive Negative Curvature Descent with Applications in Non-convex Optimization NeurIPS 2018 A Distributed Second-Order Algorithm You Can Trust ICML 2018 When Cyclic Coordinate Descent Outperforms Randomized Coordinate Descent NeurIPS 2017 Project-Out Cascaded Regression With an Application to Face Alignment CVPR 2015 An analysis on negative curvature induced by singularity in multi-layer neural-network learning NeurIPS 2010