21 citations · 24 across the 4 of their papers we have counts for
4 papers
Agreement-Based Cascading for Efficient Inference
Steven Kolawole, Don Dennis, Ameet Talwalkar +1
Adaptive inference schemes reduce the cost of machine learning inference by assigning smaller models to easier examples, attempting to avoid invocation of larger models when possib…
Progressive Ensemble Distillation: Building Ensembles for Efficient Inference
Don Kurian Dennis, Abhishek Shetty, Anish Sevekari +2
We study the problem of progressive ensemble distillation: Given a large, pretrained teacher model , we seek to decompose the model into smaller, low-inference cost student mode…
Bitrate-Constrained DRO: Beyond Worst Case Robustness To Unknown Group Shifts
Amrith Setlur, Don Dennis, Benjamin Eysenbach +4
Training machine learning models robust to distribution shifts is critical for real-world applications. Some robust training algorithms (e.g., Group DRO) specialize to group shifts…
Heterogeneity for the Win: One-Shot Federated Clustering
Don Kurian Dennis, Tian Li, Virginia Smith
In this work, we explore the unique challenges -- and opportunities -- of unsupervised federated learning (FL). We develop and analyze a one-shot federated clustering scheme, -F…