Skip to main content
Communication Theory Lab
Communication Theory Lab
Home
News
Events
People
All People
Principal Investigator
Research Scientists
Postdoctoral Fellows
Students
Visiting Scholars
Former Members
Former Members from Texas A&M University
Former Members from University of Minnesota
Collaborators
Alumni
Research
Publications
Teaching
Funding
Media
Contact Us
EF21-P
EF21-P and friends: Improved theoretical communication complexity for distributed optimization with bidirectional compression
Feb 6, 12:00
-
13:00
B9 L2 H2 H2
EF21-P
distributed optimization
gradient descent operation
In this work we focus our attention on distributed optimization problems in the context where the communication time between the server and the workers is non-negligible. We obtain novel methods supporting bidirectional compression (both from the server to the workers and vice versa) that enjoy new state-of-the-art theoretical communication complexity for convex and nonconvex problems.