Associate Professor, Queen's University
2 papers at NeurIPS 2025
We show that adaptive optimizers like RMSProp lead to fairer minima than SGD, both theoretically and empirically.
Introduced Refined Regularized Preference Optimization with a self-alignment framework to enable fine-grained alignment of large video language models by learning from their own errors.
