2 papers
cs.LG2020
Avoiding Communication in Logistic Regression
Aditya Devarakonda, James Demmel
Stochastic gradient descent (SGD) is one of the most widely used optimization methods for solving various machine learning problems. SGD solves an optimization problem by iterative…
cs.DC2017
Avoiding Synchronization in First-Order Methods for Sparse Convex Optimization
Aditya Devarakonda, Kimon Fountoulakis, James Demmel +1
Parallel computing has played an important role in speeding up convex optimization methods for big data analytics and large-scale machine learning (ML). However, the scalability of…