5 citations · 14 across the 11 of their papers we have counts for
4 papers · 2 filters
Stochastic Optimization for Spectral Risk Measures
Ronak Mehta, Vincent Roulet, Krishna Pillutla +2
Spectral risk objectives - also called -risks - allow for learning systems to interpolate between optimizing average-case performance (as in empirical risk minimization) and wor…
Statistical and Computational Guarantees for Influence Diagnostics
Jillian Fisher, Lang Liu, Krishna Pillutla +2
Influence diagnostics such as influence functions and approximate maximum influence perturbations are popular in machine learning and in AI domain applications. Influence diagnosti…
Orthogonal Statistical Learning with Self-Concordant Loss
Lang Liu, Carlos Cinelli, Zaid Harchaoui
Orthogonal statistical learning and double machine learning have emerged as general frameworks for two-stage statistical prediction in the presence of a nuisance component. We esta…
Distribution Embedding Networks for Generalization from a Diverse Set of Classification Tasks
Lang Liu, Mahdi Milani Fard, Sen Zhao
We propose Distribution Embedding Networks (DEN) for classification with small data. In the same spirit of meta-learning, DEN learns from a diverse set of training tasks with the g…