Kawika Barabin

Unwrapping ADMM: Efficient Distributed Computing via Transpose Reduction

Recent approaches to distributed model fitting rely heavily on consensus ADMM, where each node solves small sub-problems using only local data. We propose iterative methods that solve global sub-problems over an entire distributed dataset. This is possible using transpose reduction strategies that…