12 citations · 18 across the 4 of their papers we have counts for
3 papers · 1 filter
Accelerating Optimization and Reinforcement Learning with Quasi-Stochastic Approximation
Shuhang Chen, Adithya Devraj, Andrey Bernstein +1
The ODE method has been a workhorse for algorithm design and analysis since the introduction of the stochastic approximation. It is now understood that convergence theory amounts t…
Model-Free Primal-Dual Methods for Network Optimization with Application to Real-Time Optimal Power Flow
Yue Chen, Andrey Bernstein, Adithya Devraj +1
This paper examines the problem of real-time optimization of networked systems and develops online algorithms that steer the system towards the optimal trajectory without explicit…
Stochastic Variance Reduced Primal Dual Algorithms for Empirical Composition Optimization
Adithya M. Devraj, Jianshu Chen
We consider a generic empirical composition optimization problem, where there are empirical averages present both outside and inside nonlinear loss functions. Such a problem is of…