335 citations · 882 across the 15 of their papers we have counts for
5 papers · 1 filter
Solving it correctly Prevalence and Persistence of Gender Gap in Basic Mathematics in rural India
Upasak Das, Karan Singhal
Mathematical ability is among the most important determinants of prospering in the labour market. Using multiple representative datasets with learning outcomes of over 2 million ch…
What Do We Mean by Generalization in Federated Learning?
Honglin Yuan, Warren Morningstar, Lin Ning +1
Federated learning data is drawn from a distribution of distributions: clients are drawn from a meta-distribution, and their data are drawn from local data distributions. Thus gene…
Learning Federated Representations and Recommendations with Limited Negatives
Lin Ning, Karan Singhal, Ellie X. Zhou +1
Deep retrieval models are widely used for learning entity representations and recommendations. Federated learning provides a privacy-preserving way to train these models without re…
A Field Guide to Federated Optimization
Jianyu Wang, Zachary Charles, Zheng Xu +50
Federated learning and analytics are a distributed approach for collaboratively learning models (or statistics) from decentralized data, motivated by and designed for privacy prote…
Federated Reconstruction: Partially Local Federated Learning
Karan Singhal, Hakim Sidahmed, Zachary Garrett +3
Personalization methods in federated learning aim to balance the benefits of federated and local training for data availability, communication cost, and robustness to client hetero…