1 citations · 1 across the 2 of their papers we have counts for
6 papers
A Distributed Quasi-Newton Algorithm for Primal and Dual Regularized Empirical Risk Minimization
Ching-pei Lee, Cong Han Lim, Stephen J. Wright
We propose a communication- and computation-efficient distributed optimization algorithm using second-order information for solving empirical risk minimization (ERM) problems with…
First-order algorithms converge faster than on convex problems
Ching-pei Lee, Stephen J. Wright
It is well known that both gradient descent and stochastic coordinate descent achieve a global convergence rate of in the objective value, when applied to a scheme for min…
Inexact Variable Metric Stochastic Block-Coordinate Descent for Regularized Optimization
Ching-pei Lee, Stephen J. Wright
Block-coordinate descent (BCD) is a popular framework for large-scale regularized optimization problems with block-separable structure. Existing methods have several limitations. T…
A Distributed Quasi-Newton Algorithm for Empirical Risk Minimization with Nonsmooth Regularization
Ching-pei Lee, Cong Han Lim, Stephen J. Wright
We propose a communication- and computation-efficient distributed optimization algorithm using second-order information for solving ERM problems with a nonsmooth regularization ter…
Inexact Successive Quadratic Approximation for Regularized Optimization
Ching-pei Lee, Stephen J. Wright
Successive quadratic approximations, or second-order proximal methods, are useful for minimizing functions that are a sum of a smooth part and a convex, possibly nonsmooth part tha…
On the Equivalence of CoCoA+ and DisDCA
Ching-pei Lee
In this document, we show that the algorithm CoCoA+ (Ma et al., ICML, 2015) under the setting used in their experiments, which is also the best setting suggested by the authors tha…