11 citations · 51 across the 24 of their papers we have counts for
5 papers · 1 filter
Diffusion-Robust Optimization over Graphs
Liviu Aolaritei, Ricky Huang, Michael I. Jordan +1
We introduce a diffusion-based uncertainty model for robust optimization on directed graphs, in which perturbations of edge weights propagate along adjacent edges and satisfy conse…
Decision-Focused On-Policy Learning for Contextual Linear Optimization with Partial Feedback
Wyame Benslimane, Tinghan Ye, Pascal Van Hentenryck +1
Decision-focused learning (DFL) trains predictive models by optimizing downstream decision quality rather than standalone prediction accuracy. For contextual linear optimization, m…
A Barrier-Metric First-Order Method for Linearly Constrained Bilevel Optimization
Tenglong Hong, Paul Grigas
We study bilevel optimization with a fixed polyhedral lower feasible set. Such problems are challenging for two reasons: active-set changes can make the upper objective nonsmooth,…
Direct Spectral Acceleration of First-Order Methods for Saddle Point Problems with Bilinear Coupling
Meng Li, Paul Grigas
We study convex-concave saddle point problems with bilinear coupling, covering linearly constrained convex optimization and more general nonsmooth or constrained models via a proxi…
Decision-Focused Sequential Experimental Design: A Directional Uncertainty-Guided Approach
Beichen Wan, Mo Liu, Paul Grigas +1
We consider the sequential experimental design problem in the predict-then-optimize paradigm. In this paradigm, the outputs of the prediction model are used as coefficient vectors…