435 citations · 1.7k across the 22 of their papers we have counts for
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math.ST2019
Distributed Machine Learning with Sparse Heterogeneous Data
Dominic Richards, Sahand N. Negahban, Patrick Rebeschini
Motivated by distributed machine learning settings such as Federated Learning, we consider the problem of fitting a statistical model across a distributed collection of heterogeneo…
cs.LG2019★ 12 cited
Warm-starting Contextual Bandits: Robustly Combining Supervised and Bandit Feedback
Chicheng Zhang, Alekh Agarwal, Hal Daumé +2
We investigate the feasibility of learning from a mix of both fully-labeled supervised data and contextual bandit data. We specifically consider settings in which the underlying le…