second-order optimization

Second-Order Stochastic Optimization for Machine Learning in Linear Time JMLR 2017 A Kronecker-factored approximate Fisher matrix for convolution layers ICML 2016 A Multi-Batch L-BFGS Method for Machine Learning NeurIPS 2016 Efficient Second Order Online Learning by Sketching NeurIPS 2016 Newton-Stein Method: An Optimization Method for GLMs via Stein's Lemma JMLR 2016 Pymanopt: A Python Toolbox for Optimization on Manifolds using Automatic Differentiation JMLR 2016 Scalable Adaptive Stochastic Optimization Using Random Projections NeurIPS 2016 Efficient Second-Order Gradient Boosting for Conditional Random Fields AISTATS 2015 Fast Second Order Stochastic Backpropagation for Variational Inference NeurIPS 2015 Newton-Stein Method: A Second Order Method for GLMs via Stein's Lemma NeurIPS 2015 Optimizing Neural Networks with Kronecker-factored Approximate Curvature ICML 2015 Scaling up Natural Gradient by Sparsely Factorizing the Inverse Fisher Matrix ICML 2015 Second-Order Non-Stationary Online Learning for Regression JMLR 2015 Identifying and attacking the saddle point problem in high-dimensional non-convex optimization NeurIPS 2014 Least Squares Revisited: Scalable Approaches for Multi-class Prediction ICML 2014 Newton Greedy Pursuit: A Quadratic Approximation Method for Sparsity-Constrained Optimization CVPR 2014 Fast algorithms for sparse principal component analysis based on Rayleigh quotient iteration ICML 2013 Second Order Online Collaborative Filtering ACML 2013 Krylov Subspace Descent for Deep Learning AISTATS 2012 Newton-Like Methods for Sparse Inverse Covariance Estimation NeurIPS 2012 Periodic Step Size Adaptation for Single Pass On-line Learning NeurIPS 2009 SGD-QN: Careful Quasi-Newton Stochastic Gradient Descent JMLR 2009