9 papers
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…
Smart Surrogate Losses for Contextual Stochastic Linear Optimization with Robust Constraints
Hyungki Im, Wyame Benslimane, Paul Grigas
We study an extension of contextual stochastic linear optimization (CSLO) that, in contrast to most of the existing literature, involves inequality constraints that depend on uncer…