second-order method

GO Hessian for Expectation-Based Objectives AAAI 2021 Learning from Censored and Dependent Data: The case of Linear Dynamics COLT 2021 LocalNewton: Reducing communication rounds for distributed learning UAI 2021 Tensor Normal Training for Deep Learning Models NeurIPS 2021 Adaptive Online Kernel Sampling for Vertex Classification AISTATS 2020 Convex optimization based on global lower second-order models NeurIPS 2020 Second-Order Information in Non-Convex Stochastic Optimization: Power and Limitations COLT 2020 EA-CG: An Approximate Second-Order Method for Training Fully-Connected Neural Networks AAAI 2019 Limitations of the empirical Fisher approximation for natural gradient descent NeurIPS 2019 Robust Frequent Directions with Application in Online Learning JMLR 2019 Small Steps and Giant Leaps: Minimal Newton Solvers for Deep Learning ICCV 2019 The Common-directions Method for Regularized Empirical Risk Minimization JMLR 2019 A Distributed Second-Order Algorithm You Can Trust ICML 2018 Large Scale Empirical Risk Minimization via Truncated Adaptive Newton Method AISTATS 2018 Stochastic Second-Order Method for Large-Scale Nonconvex Sparse Learning Models IJCAI 2018 Efficient Second-Order Online Kernel Learning with Adaptive Embedding NeurIPS 2017 Oracle Complexity of Second-Order Methods for Finite-Sum Problems ICML 2017 Second-Order Stochastic Optimization for Machine Learning in Linear Time JMLR 2017 Efficient Second Order Online Learning by Sketching NeurIPS 2016 Newton Greedy Pursuit: A Quadratic Approximation Method for Sparsity-Constrained Optimization CVPR 2014 Nuclear Norm Minimization via Active Subspace Selection ICML 2014 QUIC & DIRTY: A Quadratic Approximation Approach for Dirty Statistical Models NeurIPS 2014 Exploiting Feature Covariance in High-Dimensional Online Learning AISTATS 2010 Periodic Step Size Adaptation for Single Pass On-line Learning NeurIPS 2009