5 citations · 11 across the 11 of their papers we have counts for
5 papers · 1 filter
A Primal-Dual Quasi-Newton Method for Exact Consensus Optimization
Mark Eisen, Aryan Mokhtari, Alejandro Ribeiro
We introduce the primal-dual quasi-Newton (PD-QN) method as an approximated second order method for solving decentralized optimization problems. The PD-QN method performs quasi-New…
Learning in Wireless Control Systems over Non-Stationary Channels
Mark Eisen, Konstantinos Gatsis, George J. Pappas +1
This paper considers a set of multiple independent control systems that are each connected over a non-stationary wireless channel. The goal is to maximize control performance over…
Large Scale Empirical Risk Minimization via Truncated Adaptive Newton Method
Mark Eisen, Aryan Mokhtari, Alejandro Ribeiro
We consider large scale empirical risk minimization (ERM) problems, where both the problem dimension and variable size is large. In these cases, most second order methods are infea…
IQN: An Incremental Quasi-Newton Method with Local Superlinear Convergence Rate
Aryan Mokhtari, Mark Eisen, Alejandro Ribeiro
The problem of minimizing an objective that can be written as the sum of a set of smooth and strongly convex functions is considered. The Incremental Quasi-Newton (IQN) method…
A Decentralized Quasi-Newton Method for Dual Formulations of Consensus Optimization
Mark Eisen, Aryan Mokhtari, Alejandro Ribeiro
This paper considers consensus optimization problems where each node of a network has access to a different summand of an aggregate cost function. Nodes try to minimize the aggrega…