2 citations · 4 across the 4 of their papers we have counts for
4 papers
Intrinisic Gradient Compression for Federated Learning
Luke Melas-Kyriazi, Franklyn Wang
Federated learning is a rapidly-growing area of research which enables a large number of clients to jointly train a machine learning model on privately-held data. One of the larges…
Recommending with Recommendations
Naveen Durvasula, Franklyn Wang, Scott Duke Kominers
Recommendation systems are a key modern application of machine learning, but they have the downside that they often draw upon sensitive user information in making their predictions…
SubseasonalClimateUSA: A Dataset for Subseasonal Forecasting and Benchmarking
Soukayna Mouatadid, Paulo Orenstein, Genevieve Flaspohler +8
Subseasonal forecasting of the weather two to six weeks in advance is critical for resource allocation and advance disaster notice but poses many challenges for the forecasting com…
Generalization by Recognizing Confusion
Daniel Chiu, Franklyn Wang, Scott Duke Kominers
A recently-proposed technique called self-adaptive training augments modern neural networks by allowing them to adjust training labels on the fly, to avoid overfitting to samples t…