1 citations · 1 across the 2 of their papers we have counts for
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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…
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 $X \subseteq \bbr^n$ is simple and easy to project onto, it rema…
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…
Accelerated stochastic approximation with state-dependent noise
Sasila Ilandarideva, Anatoli Juditsky, Guanghui Lan +1
We consider a class of stochastic smooth convex optimization problems under rather general assumptions on the noise in the stochastic gradient observation. As opposed to the classi…