1 citations · 1 across the 1 of their papers we have counts for
4 papers
Projection-Free Functional Constrained Optimization for Risk Aversion and Sparsity Control
Yi Cheng, Guanghui Lan, Saeed Masiha +1
We study projection-free methods for functional constrained optimization with convex or smooth nonconvex objectives. Such problems arise in applications such as portfolio optimizat…
Policy Optimization over General State and Action Spaces
Caleb Ju, Guanghui Lan
Reinforcement learning (RL) problems over general state and action spaces are notoriously challenging. In contrast to the tableau setting, one can not enumerate all the states and…
Solving Convex Smooth Function Constrained Optimization Is Almost As Easy As Unconstrained Optimization
Zhe Zhang, Guanghui Lan
While Nesterov's Accelerated Gradient Descent (AGD) efficiently solves constrained problems when the constraint set is simple and easy to project onto, i…
Dual dynamic programming for stochastic programs over an infinite horizon
Caleb Ju, Guanghui Lan
We consider solving stochastic programs over an infinite horizon. By leveraging the stationarity of the problem, we develop a novel continually-exploring infinite-horizon explorati…