11 citations · 51 across the 24 of their papers we have counts for
5 papers · 1 filter
New Methods for Parametric Optimization via Differential Equations
Heyuan Liu, Paul Grigas
We develop and analyze several different second-order algorithms for computing a near-optimal solution path of a convex parametric optimization problem with smooth Hessian. Our alg…
Binary Classification with Instance and Label Dependent Label Noise
Hyungki Im, Paul Grigas
Learning with label dependent label noise has been extensively explored in both theory and practice; however, dealing with instance (i.e., feature) and label dependent label noise…
Stochastic First-Order Algorithms for Constrained Distributionally Robust Optimization
Hyungki Im, Paul Grigas
We consider distributionally robust optimization (DRO) problems, reformulated as distributionally robust feasibility (DRF) problems, with multiple expectation constraints. We propo…
On the Softplus Penalty for Constrained Convex Optimization
Meng Li, Paul Grigas, Alper Atamturk
We study a new penalty reformulation of constrained convex optimization based on the softplus penalty function. We develop novel and tight upper bounds on the objective value gap a…
Active Learning For Contextual Linear Optimization: A Margin-Based Approach
Mo Liu, Paul Grigas, Heyuan Liu +1
We develop the first active learning method for contextual linear optimization. Specifically, we introduce a label acquisition algorithm that sequentially decides whether to reques…