29 citations · 67 across the 6 of their papers we have counts for
5 papers · 1 filter
Online Primal-Dual Mirror Descent under Stochastic Constraints
Xiaohan Wei, Hao Yu, Michael J. Neely
We consider online convex optimization with stochastic constraints where the objective functions are arbitrarily time-varying and the constraint functions are independent and ident…
Solving Non-smooth Constrained Programs with Lower Complexity than : A Primal-Dual Homotopy Smoothing Approach
Xiaohan Wei, Hao Yu, Qing Ling +1
We propose a new primal-dual homotopy smoothing algorithm for a linearly constrained convex program, where neither the primal nor the dual function has to be smooth or strongly con…
Primal-Dual Frank-Wolfe for Constrained Stochastic Programs with Convex and Non-convex Objectives
Xiaohan Wei, Michael J. Neely
We study constrained stochastic programs where the decision vector at each time slot cannot be chosen freely but is tied to the realization of an underlying random state vector. Th…
Online Learning in Weakly Coupled Markov Decision Processes: A Convergence Time Study
Xiaohan Wei, Hao Yu, Michael J. Neely
We consider multiple parallel Markov decision processes (MDPs) coupled by global constraints, where the time varying objective and constraint functions can only be observed after t…
Online Convex Optimization with Stochastic Constraints
Hao Yu, Michael J. Neely, Xiaohan Wei
This paper considers online convex optimization (OCO) with stochastic constraints, which generalizes Zinkevich's OCO over a known simple fixed set by introducing multiple stochasti…