3 papers
math.OC2026
Robust Chance-Constrained Optimization using a Continuous Parameter Space Wasserstein-2 Ambiguity Set of Gaussian Mixtures
Shibshankar Dey, Sanjay Mehrotra
We study distributionally robust linear chance-constrained problems in which uncertainty is modeled by a Gaussian mixture model (GMM). Finite-support distributionally robust (FDR)…
cs.LG2026
Do Deep Networks Forget Initialization? A Forgetting-Time View of Practical Inductive Bias
Mohua Das, Pierfrancesco Beneventano, Shibshankar Dey +2
Randomly initialized neural networks induce a prior over functions, but the predictor used in practice is produced only after training. We ask how much of this initial bias survive…
math.OC2025
On Solving Chance-Constrained Models with Gaussian Mixture Distribution
Shibshankar Dey, Sanjay Mehrotra, Anirudh Subramanyam
We study linear chance-constrained problems where the coefficients follow a Gaussian mixture distribution. We provide mixed-binary quadratic programs that give inner and outer appr…