Efficient Distributed Learning with Sparsity

Jialei Wang, Mladen Kolar, Nathan Srebro, Tong Zhang

Abstract: We propose a novel, efficient approach for distributed sparse learning with observations randomly partitioned across machines. In each round of the proposed method, worker machines compute the grad...