Efficient Distributed Algorithms for Convex Optimization with Improved Bit Complexity

The authors develop efficient distributed algorithms for fundamental convex optimization problems, including least squares regression, low-rank approximation, linear programming, and finite-sum minimization, with improved communication complexity in terms of the total number of bits exchanged.