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stat.ML2026
FairBED: A Bayesian Experimental Design Approach to Gathering Fairer Data
Marcel Hedman, Emily Alger, Brieuc Lehmann +2
Frameworks for ensuring fairness in machine learning typically focus on learning fair models from existing data. But this endeavor is often undermined by biases already present in…
stat.ML2025
Step-DAD: Semi-Amortized Policy-Based Bayesian Experimental Design
Marcel Hedman, Desi R. Ivanova, Cong Guan +1
We develop a semi-amortized, policy-based, approach to Bayesian experimental design (BED) called Stepwise Deep Adaptive Design (Step-DAD). Like existing, fully amortized, policy-ba…