1 citations · 1 across the 3 of their papers we have counts for
3 papers
stat.ML2025
A Generalization Theory for Zero-Shot Prediction
Ronak Mehta, Zaid Harchaoui
A modern paradigm for generalization in machine learning and AI consists of pre-training a task-agnostic foundation model, generally obtained using self-supervised and multimodal c…
cs.LG2025
Supervised Stochastic Gradient Algorithms for Multi-Trial Source Separation
Ronak Mehta, Mateus Piovezan Otto, Noah Stanis +2
We develop a stochastic algorithm for independent component analysis that incorporates multi-trial supervision, which is available in many scientific contexts. The method blends a…
stat.ML2023★ 1 cited
Distributionally Robust Optimization with Bias and Variance Reduction
Ronak Mehta, Vincent Roulet, Krishna Pillutla +1
We consider the distributionally robust optimization (DRO) problem with spectral risk-based uncertainty set and -divergence penalty. This formulation includes common risk-sensit…