3 problems

Consider AdaGrad applied to smooth convex optimization problems with stochastic gradient noise whose bounded $\alpha$-th moment satisfies $\alpha<2$, and let $b_t$ denote the adapt…

Stochastic optimization methods such as Adam and Clip-SGD use adaptive stepsizes, and Clip-SGD is known to converge in expectation when the gradient noise has a bounded $\alpha$-th…

Logarithmic-factor improvement conjecture. Adjusting the proof technique from Nguyen et al. should improve the logarithmic factors in the authors' results as well.