An asynchronous mini-batch algorithm for regularized stochastic optimization

Mini-batch optimization has proven to be a powerful paradigm for large-scale learning. However, the state of the art mini-batch algorithms assume synchronous operation or cyclic update orders. When worker nodes are heterogeneous (due to different computational capabilities, or different communicatio... View More