newton method

The Physical Systems Behind Optimization Algorithms NeurIPS 2018 Towards a Mathematical Understanding of the Difficulty in Learning With Feedforward Neural Networks CVPR 2018 Approximate Newton Methods and Their Local Convergence ICML 2017 A Study on Trust Region Update Rules in Newton Methods for Large-scale Linear Classification ACML 2017 Newton-Type Methods for Inference in Higher-Order Markov Random Fields CVPR 2017 Tensor Balancing on Statistical Manifold ICML 2017 Adaptive Newton Method for Empirical Risk Minimization to Statistical Accuracy NeurIPS 2016 Efficient Second Order Online Learning by Sketching NeurIPS 2016 Large-Scale Optimization Algorithms for Sparse Conditional Gaussian Graphical Models AISTATS 2016 SDNA: Stochastic Dual Newton Ascent for Empirical Risk Minimization ICML 2016 Sub-sampled Newton Methods with Non-uniform Sampling NeurIPS 2016 Convergence rates of sub-sampled Newton methods NeurIPS 2015 DiSCO: Distributed Optimization for Self-Concordant Empirical Loss ICML 2015 Communication-Efficient Distributed Optimization using an Approximate Newton-type Method ICML 2014 Identifying and attacking the saddle point problem in high-dimensional non-convex optimization NeurIPS 2014 Newton Greedy Pursuit: A Quadratic Approximation Method for Sparsity-Constrained Optimization CVPR 2014 An Improved GLMNET for L1-regularized Logistic Regression JMLR 2012 A Unifying Perspective of Parametric Policy Search Methods for Markov Decision Processes NeurIPS 2012 Newton-Like Methods for Sparse Inverse Covariance Estimation NeurIPS 2012 Proximal Newton-type methods for convex optimization NeurIPS 2012 A Finite Newton Algorithm for Non-degenerate Piecewise Linear Systems AISTATS 2011 Sparse Inverse Covariance Matrix Estimation Using Quadratic Approximation NeurIPS 2011 Exact 1-Norm Support Vector Machines Via Unconstrained Convex Differentiable Minimization JMLR 2006