18 citations · 20 across the 3 of their papers we have counts for
3 papers
cs.IR2022★ 18 cited
RGRecSys: A Toolkit for Robustness Evaluation of Recommender Systems
Zohreh Ovaisi, Shelby Heinecke, Jia Li +3
Robust machine learning is an increasingly important topic that focuses on developing models resilient to various forms of imperfect data. Due to the pervasiveness of recommender s…
cs.LG2020
Communication-Aware Collaborative Learning
Avrim Blum, Shelby Heinecke, Lev Reyzin
Algorithms for noiseless collaborative PAC learning have been analyzed and optimized in recent years with respect to sample complexity. In this paper, we study collaborative PAC le…
cs.LG2019★ 2 cited
Crowdsourced PAC Learning under Classification Noise
Shelby Heinecke, Lev Reyzin
In this paper, we analyze PAC learnability from labels produced by crowdsourcing. In our setting, unlabeled examples are drawn from a distribution and labels are crowdsourced from…