Search Results for author:
Found 4 papers, 2 papers with code
The radius of statistical efficiency
Classical results in asymptotic statistics show that the Fisher information matrix controls the difficulty of estimating a statistical model from observed data.
Stochastic Approximation with Decision-Dependent Distributions: Asymptotic Normality and Optimality
We show that under mild assumptions, the deviation between the average iterate of the algorithm and the solution is asymptotically normal, with a covariance that clearly decouples the effects of the gradient noise and the distributional shift.
Stochastic Optimization under Distributional Drift
We consider the problem of minimizing a convex function that is evolving according to unknown and possibly stochastic dynamics, which may depend jointly on time and on the decision variable itself.
Stochastic optimization under time drift: iterate averaging, step-decay schedules, and high probability guarantees
We consider the problem of minimizing a convex function that is evolving in time according to unknown and possibly stochastic dynamics.
