Associate Professor, Columbia University
2 papers at NeurIPS 2025
This paper is a local misspecificiation analysis of three data-driven stochastic optimization methods.
Our paper shows that ensemble learning via majority voting achieves exponentially faster risk decay, improving base learners with slow rates.