Systems | Information | Learning | Optimization
 

Balancing Computation and Communication in Distributed Optimization

Distributed optimization methods consist of two key aspects: communication and computation. More specifically, at every iteration (or every several iterations) of a distributed algorithm, each node in the network requires some form of information exchange with its neighboring nodes (communication) and the computation of a (sub)-gradient (computation). The standard way …

Analysis and Design of First-Order Methods for Smooth Strongly Convex Optimization & Low-Complexity Channel Estimation via the Sparse Fast Fourier Transform

Optimization algorithms play a fundamental role in analyzing the vast amount of data available today. Due to the need for fast optimization algorithms, there has been recent interest in understanding the mechanisms which enable optimization algorithms to converge quickly. We gain insight into these algorithms by leveraging techniques from control …