On the Convergence of mSGD and AdaGrad for Stochastic Optimization

Ruinan Jin, Yu Xing, Xingkang He

As one of the most fundamental stochastic optimization algorithms, stochastic gradient descent (SGD) has been intensively developed and extensively applied in machine learning in t…