4 papers
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…
GDC Cohort Copilot: An AI Copilot for Curating Cohorts from the Genomic Data Commons
Steven Song, Anirudh Subramanyam, Zhenyu Zhang +2
The Genomic Data Commons (GDC) provides access to high quality, harmonized cancer genomics data through a unified curation and analysis platform centered around patient cohorts. Wh…
Reduced Sample Complexity in Scenario-Based Control System Design via Constraint Scaling
Jaeseok Choi, Anand Deo, Constantino Lagoa +1
The scenario approach is widely used in robust control system design and chance-constrained optimization, maintaining convexity without requiring assumptions about the probability…
LaB-RAG: Label Boosted Retrieval Augmented Generation for Radiology Report Generation
Steven Song, Anirudh Subramanyam, Irene Madejski +1
In the current paradigm of image captioning, deep learning models are trained to generate text from image embeddings of latent features. We challenge the assumption that fine-tunin…