This work considers multi-agent sharing optimization problems, where each agent owns a
local smooth function plus a non-smooth function, and the network seeks to minimize the …

In this article, we consider a multi-node sharing problem, where each node possesses a
local smooth function that is further considered as the average of several constituent …

As electronic technology advances, a growing number of consumer electronics products
emerge. Accurate and trustworthy consumer electronics product recommendation can …

We investigate the distributed multi-agent sharing optimization problem in a directed graph,
with a composite objective function consisting of a smooth function plus a convex (possibly …

We develop a new algorithm for distributed learning with non-smooth regularizers and
feature partitioning. To this end, we transform the underlying optimization problem into a …

We develop a new consensus-based distributed algorithm for solving learning problems
with feature partitioning and non-smooth convex objective functions. Such learning …

This thesis proposes machine learning algorithms that can be fully distributed over ad-hoc
networks of machines/agents. Developing distributed algorithms for artificial intelligence is …

In this chapter, we consider a multi-node sharing problem, where each node possesses a
local smooth function that is further considered as the average of several constituent …