3 papers
cs.LG2017
Accelerated Dual Learning by Homotopic Initialization
Hadi Daneshmand, Hamed Hassani, Thomas Hofmann
Gradient descent and coordinate descent are well understood in terms of their asymptotic behavior, but less so in a transient regime often used for approximations in machine learni…
cs.LG2016
Adaptive Newton Method for Empirical Risk Minimization to Statistical Accuracy
Aryan Mokhtari, Alejandro Ribeiro
We consider empirical risk minimization for large-scale datasets. We introduce Ada Newton as an adaptive algorithm that uses Newton's method with adaptive sample sizes. The main id…
cs.LG2016
DynaNewton - Accelerating Newton's Method for Machine Learning
Hadi Daneshmand, Aurelien Lucchi, Thomas Hofmann
Newton's method is a fundamental technique in optimization with quadratic convergence within a neighborhood around the optimum. However reaching this neighborhood is often slow and…